Limitations of previously used MCSA-based fault diagnosis techniques considering environment impacts.
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More than half of the publishers listed alongside IntechOpen (18 out of 30) are Social Science and Humanities publishers. IntechOpen is an exception to this as a leader in not only Open Access content but Open Access content across all scientific disciplines, including Physical Sciences, Engineering and Technology, Health Sciences, Life Science, and Social Sciences and Humanities.
\\n\\nOur breakdown of titles published demonstrates this with 47% PET, 31% HS, 18% LS, and 4% SSH books published.
\\n\\n“Even though ItechOpen has shown the potential of sci-tech books using an OA approach,” other publishers “have shown little interest in OA books.”
\\n\\nAdditionally, each book published by IntechOpen contains original content and research findings.
\\n\\nWe are honored to be among such prestigious publishers and we hope to continue to spearhead that growth in our quest to promote Open Access as a true pioneer in OA book publishing.
\\n\\n\\n\\n
\\n"}]',published:!0,mainMedia:null},components:[{type:"htmlEditorComponent",content:'
Simba Information has released its Open Access Book Publishing 2020 - 2024 report and has again identified IntechOpen as the world’s largest Open Access book publisher by title count.
\n\nSimba Information is a leading provider for market intelligence and forecasts in the media and publishing industry. The report, published every year, provides an overview and financial outlook for the global professional e-book publishing market.
\n\nIntechOpen, De Gruyter, and Frontiers are the largest OA book publishers by title count, with IntechOpen coming in at first place with 5,101 OA books published, a good 1,782 titles ahead of the nearest competitor.
\n\nSince the first Open Access Book Publishing report published in 2016, IntechOpen has held the top stop each year.
\n\n\n\nMore than half of the publishers listed alongside IntechOpen (18 out of 30) are Social Science and Humanities publishers. IntechOpen is an exception to this as a leader in not only Open Access content but Open Access content across all scientific disciplines, including Physical Sciences, Engineering and Technology, Health Sciences, Life Science, and Social Sciences and Humanities.
\n\nOur breakdown of titles published demonstrates this with 47% PET, 31% HS, 18% LS, and 4% SSH books published.
\n\n“Even though ItechOpen has shown the potential of sci-tech books using an OA approach,” other publishers “have shown little interest in OA books.”
\n\nAdditionally, each book published by IntechOpen contains original content and research findings.
\n\nWe are honored to be among such prestigious publishers and we hope to continue to spearhead that growth in our quest to promote Open Access as a true pioneer in OA book publishing.
\n\n\n\n
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Induction motors are the industry workhorse due to the fact that they are rugged, reliable and economical. Induction motors are used in industry for conversion of electrical energy into mechanical energy [1]. As shown in Figure 1, induction motors are being used in various applications, such as in the nuclear power plants, aviation industry, transportation industry, mining industry, chemical processing plants, paper mills and the petroleum industry [1].
Applications of induction motors.
The operation of induction motor in harsh industrial environment affects its reliability and has been a critical issue. The unexpected breakdown of induction motor might result in the disturbance of critical services such as medical applications, transportation military operations and aviation. An unexpected breakdown of a motor might result in costly maintenance or loss of life in applications where continuous process is needed and where down-time is not tolerable. The induction motors require only basic maintenance and have a very low failure rate. However, the burning of the motors causes a great deal of unacceptable production loss. Consequently, diagnosing incipient faults will prevent the problems of unexpected breakdowns of the machines and it helps in reducing the maintenance costs. As reported in [2], 50% of operating cost of manufacturing and processing plants is related to maintenance. Therefore, this is a major area of concern in industries. The researchers are constantly looking for new techniques to minimize the unexpected machine failures and maintenance cost.
The scheduled replacement, scheduled maintenance and condition-based maintenance are the basic methods used in the industry for reliable operations of the machines. The scheduled replacement is a simple but expensive method as the replacement of machine parts is conducted on a regular basis. In the scheduled maintenance method, the checking and/or overhauling of the equipment has to be done on a regular basis and this method is widely used in industry as it is less expensive as compared to the scheduled replacement. The condition-based maintenance method determines the machine condition by taking measurements using sensors. By this method, the time periods between maintenance can be increased and machines can be monitored continuously so that maintenance can be scheduled on a needed basis. Condition monitoring (CM) is a method used in condition-based maintenance (CBM). It is an effective type of predictive maintenance (PM). The main steps involved in PM are shown in Figure 2.
Activities in predictive maintenance.
Normally, the condition monitoring maintenance process would be monitoring the specific parameters like vibration, overheating, over current of equipment for early sign of coming failures and to predict the need of maintenance before rigorous failures. CM could be performed through visual inspection or through sophisticated fault diagnosis system. CM is suitable for continuous process plants where machine breakdowns can be very costly.
The methods of condition monitoring are categorized into two primary classifications, namely the offline tests and the online tests. The offline tests are performed by isolating the machine from main AC power supply. Although this is a comprehensive approach, sometimes causes unnecessary shutdowns on machines. Alternatively, the sensors which are installed on the machine are used to detect faults for online condition monitoring and fault diagnosis in an induction motors during the operation of the machine. The online tests cause fewer disturbances than offline tests but the results produced from online testing are more complicated and their interpretation is difficult than the offline tests. Over the past two decades, there has been an abundance of research work done in the online condition monitoring techniques for diagnosing problems in induction motors. For the detection of various faults usually affecting machines, several different techniques have been not only proposed but also used successfully. However, a good understanding of the mechanical and electrical properties of the machine in healthy and faulty conditions dramatically influences the accuracy and reliability of the online condition monitoring methods [3, 4]. Online condition monitoring techniques can be classified into two categories: firstly the classical method and secondly the digital method [4]. In classical method, electromechanical devices are used to protect the motors. The electromechanical devices are expensive, less efficient, having very slow response and not reliable as some of the devices have even shorter life than the motor itself. The digital method is the latest method for the condition monitoring and involves integrated circuits, micro-controllers, micro-processors and programmable logic controllers.
An induction motor is normally composed of the following parts: frame, stator, winding, rotor and bearings. The structure of induction motor is shown in Figure 3. Induction motors are used in almost all types of industries. Induction motor is an asynchronous machine made up of a magnetic circuit that is joined to two electrical circuits; these circuits rotate with respect to each other. Electromagnetic induction is used to pass power from one circuit to the other. These electric motors are used to convert electrical energy into mechanical energy [5]. The conversion of energy is dependent upon the natural presence of the phenomena connecting magnetic and electrical fields in one side while motion and mechanical force are connected into the other side. On the basis of types of rotor winding, induction motors can be placed into two categories. They are the wound-rotor induction motors and squirrel-cage motors [6].
The structure of induction motor [5].
The squirrel cage induction motor is made up of conducting bars that are placed in slots of the rotor body. These conducting bars are short circuited through end rings. Magnesium, copper, or aluminium alloys are the materials usually used in manufacturing of the rotor bars. Another kind of rotor is known as a form-wound rotor since it possesses a poly-phase winding much like that of the winding of the stator. There are three slip rings which are joined to the winding of the rotor shaft. In a form-wound rotor, the slip rings are joined to a variable resistance and can restrict the current as well as the heating of the rotor [6].
The squirrel-cage induction motor is economical and robust than the wound-rotor induction motor. At constant supply of voltages and frequency, squirrel-cage induction motor runs at a constant speed. In this motor, if there is an increase in the load torque, the speed will decrease slightly. Therefore, it is appropriate to be used in drive systems that run at a constant speed [5, 6]. However, a variety of applications used in industrial areas need adjustable speeds drives. Traditionally, it is a direct current (DC) motor that is utilized in adjustable drive system. However, DC motors are expensive and possess carbon brushes that must be frequently maintained. As squirrel cage induction motors have no brushes so they are cheap and are preferred for high speed applications. Furthermore, due to the availability of solid state controllers, mostly high speed drive systems use squirrel cage induction motors. This type of induction motor is extensively utilized in drive applications of both low and high performance due to its versatility and ruggedness. Induction motors are suitable for almost all commercial and industrial applications due to their construction being so simple and they have only a few parts, which reduce the cost of maintenance. Applications in both adjustable-speed drive (ASD) and constant-speed drive are the main uses of induction motors.
Induction motors are often exposed to operating environments that may not be ideal and in some cases are even harsh. These situations could be due to insufficient cooling, inadequate lubrication, structure vibration, overload, frequent motor starts and stops, etc. In such situations, induction motors are put under detrimental stresses which can lead to failure [7, 8]. Because of the significant role that motors play in various applications, improvement in the reliability of motors is required. The reasons why electric motors fail in industry have been commonly reported as follows [9–11]
Wrong-rated power, voltage and current
Mistakes during repairs
Unstable supply voltage or current source
Post the standard lifetime
Overload or unbalanced load
Electrical stress from fast switching inverters or unstable ground
Residual stress from manufacturing
Harsh application environment
As induction motor is most often symmetrical, so faults in the motor normally disturb the symmetry of the motor. Burning of motors in the industry could be due to following reasons: thermal overloading, overloading due to undesirable stresses, air-gap eccentricity, speed oscillations, stator winding failure, broken rotor bars, bearing failure, coupled gear failures and unbalanced voltages. A concise discussion is made regarding these defects based on how important they are with regard to the condition monitoring of induction motors. According to a survey conducted in 2005 by the Electric Power Research Institute, more than 40% burning of AC motors is due to the failure of bearings (more than 50% burning of the motor is due to mechanical defects, i.e. bearing defects, gear defects, belt and pulley defects). The summary of the survey report is shown in Figure 4 [2, 3, 12].
EPRI survey report 2005 [2, 3, 12].
As stated in Peter Vas [13] and P.J. Tavner and J. Penman [14], the defects of the motor are categorized into two groups.
Mechanical defects
Electrical defects
Air gap eccentricities, bearing defects, shaft misalignment and abnormalities at the mechanical transmission system are included in the list of mechanical defects. Broken rotor bar and stator winding defects are included in the list of electrical defects. The detail of these defects is discussed in following subsections.
The typical examples of mechanical defects that usually occur in an induction motor are presented as below.
Bearings are widely used in rotating machinery across various industries that include paper, textile, aerospace, nuclear power plants, oil refineries, offshore pumping stations, steel, railways, construction, mining and renewable energy. The defects in the bearings cause breakdown of rotating machinery, which results in significant economic losses and in certain situations loss of human lives; for example, when a train derails or an aircraft engine fails due to a bearing defect. Bearings are typical components found in the motors that are used to allow for the shaft rotation. Majority of the motor failure is due to the bearing malfunctions. Bearings as shown in Figure 5 are made up of inner and outer races. Several rolling elements (balls) are placed in between these two races. Cage is used to keep the balls moving at equal distance from each other. Normally, stresses developed in the motor causes fatigue in the bearing races. This fatigue causes localized defects (single-point defects like spalling or pitting or dents or holes) and distributed defects (generalized surface roughness) in the bearings of the motor [15–17].
The structure of ball bearing.
The localized defects are induced mainly due to the operational wear (contact fatigue) of bearings. If the bearings are properly installed, kept free of contamination and well lubricated during operation then bearing failure will occur only after the pre-determined life (millions of cycles) of the bearing. This type of failure initially starts in a subsurface at micro-scale level at a single-point and then due to continuous stress cycles, they eventually cause material to break. These single-point defects are characterized as spalling or pitting or localized defect [15–21]. Littman [22, 23] characterized as micro-scale subsurface defects as spalls and macro-scale surface originated defects as pitting. These types of faults produce impulsive type of vibration and serve as indication of incipient failure and due to this reason many fault diagnosis techniques have been developed to diagnose these types of faults.
The distributed defects are induced due to the manufacturing errors or due to contamination, improper lubrication, corrosion, electrical fluting and misalignment during running operation of the bearing. In these types of faults, the magnitude of the contact force between race and ball varies continuously during shaft rotation. Distributed faults create continuous type of vibration and cause premature failure of the motor bearings and thus it is important to develop a suitable condition monitoring scheme to diagnose these types of faults. Figure 6 shows the example of typical localized and distributed defects in bearings of induction motor.
Example of bearing (a) localized defects and (b) distributed defects.
Vibration and noise are generated in the motor due to these defects [24]. The failure of bearings can also occur due to high bearing temperature. The temperature of the bearings should not increase beyond specific degrees at rated conditions. An example of this would be in the petroleum and chemical industries where the IEEE 841 standard specifies that the rise in temperature of the bearings under a rated load should not go above 45°C. Rise in the winding temperature, improper lubrication, the distribution of the temperature within the motor and the operating speed of the motor are the main factors for the rise of the bearing temperature. Consequently, the bearing temperature measurements can give helpful data to estimate the health of the bearings as well as health of the motor [25, 26].
Air-gap eccentricity is a typical defect found in the rotor of the motor. Noise and vibration in the motor structure are usually produced due to eccentricity. For the healthy motors, the centre of the rotor and stator bore is perfectly aligned. Moreover, the centre of rotation for the rotor is the same as the stator bore centre. If the rotor is not aligned centrally, radial forces or magnetic pull will be developed, which causes the rotor-stator rub resulting in the damage of rotor and stator [27]. As demonstrated in Ref. [28] air-gap eccentricities are of three kinds
Dynamic eccentricity
Static eccentricity
Mixed eccentricity
A dynamic eccentricity as shown in Figure 7 results in an unbalanced magnetic pull (UMP) that acts on the rotor. The rotation of the UMP is similar to the rotation of the motor. The UMP can be easily monitored via current or vibration analysis. On the other hand, eccentricity that is static possesses a constant pull in only one direction, which also causes a UMP. However, it is not easy to detect this type of UMP [29].
Example of (a) static eccentricity and (b) dynamic eccentricity [29].
Sometimes, dynamic and static eccentricities often exist together. Moreover, one can never assume that ideal centric conditions exist. Therefore, a certain amount of eccentricity is always expected in any real motor. This combination of eccentricities such as dynamic and static is known as mixed eccentricity.
Detecting abnormalities at the mechanical transmission system has been a vital area of study for quite a long time. Mechanical loads and gears are frequently connected to motors and a variety of faults such as defected gearing system, belt-pulley system and coupling misalignment are possible in these mechanical arrangements. An example of the gear fault is shown in Figure 8. In some applications like in aircraft, the condition monitoring of gears coupled with drive system is very much important to enhance the reliability of the gear [30]. Gear failures tend to occur when a gear is working under high stress conditions. The common gear faults are related to gear tooth irregularities namely chipped tooth, root crack, spalling, wear, pitting, tooth surface damage and broken tooth. Gear faults usually have significant effects on power transmission. They create disablement of the drives, which often causes damage to other gearbox components such as the shaft, bearing, etc., by pieces of the broken tooth. The tooth breakage can be due to overload or impact and damage.
Example of the gear defects [30].
The following subsections give some of the typical examples of electrical defects in induction motors.
The general belief is that damage in the insulation of the winding turns contributes majority of the defects related to stator. This kind of defect is known as a ‘stator turn defect’ [31]. In a symmetrical induction motor, a stator turn fault produces a huge amount of current to flow through turns which creates too much heat in the shorted turns. The motor will burn if this heat, which is in direct proportion to the square of the current, is more than the threshold value [32]. An example of the stator related fault is shown in Figure 9.
The stator fault in induction motor [31].
In induction motors, the insulation used in stator winding is subjected to degradation due to contamination, transient voltage stresses on the insulating material, mechanical stresses and thermal overloading. Notably, thermal stresses are the primary cause for the deterioration of the insulation in the winding of the stator. Insulation even of the best quality could experience a rapid failure if the motor is run at a temperature greater than its threshold value. Generally, the life time of the insulation is decreased by 50% for every 10°C increase over the threshold value of the temperature of stator winding [33]. Therefore, monitoring the temperature of the winding of the stator is vital so that the motor will not run at a level greater than its thermal capacity. To accomplish this, several methods have been introduced. However, these methods could not identify the exact heating-point at the earliest stage [34, 35].
Some factors that speed up the deterioration of the insulation include the defected bearings, broken rotor bars, vibrations of the rotor, movement of a coil and misalignment of the rotor and air-gap eccentricity [36]. Consequently, these mechanical failures should be identified before they cause the failure of the insulation in the stator winding [37, 38]. Another problem for the insulation is foreign materials such as dust and bearing grease which can cause contaminations over the insulation of the stator. This contamination could possibly cause the reduction in dissipation of heat from the stator winding [39]. Due to this reason it is recommended that all the motors should be kept clean and dry.
Most often, the rotor bars in lower rated motors are produced by methods of die casting. However, the rotor bars of high rating motors are manufactured using copper. Producing rotor bars using methods of die casting has been found to cause a variety of technologically problems. Asymmetries in the rotor of the induction motors have been found which were caused by either technological problems, or because of the melting of end rings or bars. On the other hand, there is abundance of other factors causing the failure of rotors. Some of these are listed below [12, 13]
Metallurgical stresses that are non-uniform could possibly be created in the assembly of the cage during manufacturing process and these stresses could result in a failure while the motor is operating later on.
When thermal stresses are put on the rotor bar at the start-up of the motor, the rotor might not be capable of moving longitudinally in its slot.
Some stresses could be developed on the rotor bars due to heavy end rings.
The reasons mentioned above could cause damage to the bars of the rotor and at the same time cause the rotor to become unbalanced. Furthermore, asymmetrical rotor currents are produced due to asymmetry on the cage of the rotor. Because of this, damage to just one rotor bar could result in damage to the surrounding bars. This damage could then spread, resulting in fractures in several rotor bars. Cracks in bars cause overheating of the bar due to which the bar may break. Consequently, the bars in the surrounding area will begin to carry higher currents subjecting them to even greater mechanical and thermal stresses. These stresses can start cracking in rotor bars and rotor lamination will be damaged as well [13]. The distribution of the temperature throughout the lamination of the rotor is also altered because of the asymmetry of the rotor. Bar fractures can take place at different areas on the rotor. During frequent starts of the motor, the chances of fracture in the rotor end rings increase [28]. Typical example of rotor faults is shown in Figure 10.
Example of rotor fault in induction motor [13].
Continuously evaluating the health status of an industrial plant and its machinery throughout the entirety of its service is known as condition monitoring. Incipient failure detection is a vital process by which detection of defects in the early stages of their development is possible [13]. Fault diagnosis of the induction motor with some comprehensive condition monitoring system is becoming even more vital. An early alert about forthcoming failure is possible through the use of condition monitoring system. Furthermore, scheduling of preventive maintenance of the machines is also possible. Optimal preventive maintenance schedules are the result of this and also lead to the least amount of down-time on the machines [14]. Moreover, condition monitoring system gives indication to maintenance staff to arrange the required spare parts before serious breakdown occur on the machine, thus reduces overall down-time. Consequently, to improve productivity, reliability and safety of electric machines, a suitable condition monitoring system is essential. A tremendous significance has been put on by condition monitoring system in the environment of business because of several reasons that are listed below [13, 14]:
To decrease the maintenance cost
To determine the failure of machinery
To enhance the reliability of both the machines and their parts
To optimally use manpower and machine spare parts
To maximize the performance of the machinery
To enhance the failure prediction accuracy
The usage of condition monitoring for both mechanical and electrical machinery is not new. While there have been a variety of techniques developed and improved over time, invasive techniques such as acoustic emission analysis, noise analysis, thermal analysis, chemical analysis and vibration analysis, and non-invasive techniques such as motor current signature analysis (MCSA), stator current Park vector analysis and instantaneous power analysis (IPA) are considered as the most prominent methods in steady state operation conditions. The structure representing various motor faults and fault diagnosis techniques is shown in Figure 11.
The structure representing various motor faults and fault diagnosis techniques.
It has been observed that even though invasive condition monitoring and fault diagnosis techniques are optimal for the diagnosis of bearing localized and distributed defects, however, costly sensors and their associated wiring is the major disadvantage of these methods [40–45]. For example, vibration sensors (accelerometers, velocity transducers) which are integral part of this technique are too much expensive. As a result, the use of invasive fault diagnosis methods is restricted in a variety of applications. This is particularly so with applications using small sized motors as cost has an important role to play when making the decision as to which technique of condition monitoring is to be used. Another disadvantage of these techniques is that sensors need to be installed on the machine, and so it needs access to machine which is not possible in every application. Sensor needs to be mounted on the machine rightly for accurate results. As sensors also have some life period after which they fail, in this aspect, bearing life period is more significant than sensor life period [46–51].
Thus, the focus of this chapter is on the development of non-invasive condition monitoring and fault diagnosis method for induction motors.
Induction motor defects can be diagnosed via its terminal quantities, such as voltage, current, discharge and power, measurable outside the motor to give an indication of its condition. A fault in motor (i.e. in bearings or gears) produces a distortion of the electromagnetic field in the radial and circumferential plane due to which harmonic frequencies appear in the stator current and in instantaneous power. The stator current or instantaneous power of the healthy motor would have a single component of supply frequency (fundamental component). Motor faults will modulate the air-gap flux distribution which causes forward and backward rotating magnetic field and as a result side-band harmonic frequencies appear around fundamental component. Faults in the motor will generate one-side band below the supply frequency which is called lower-side band (LSB) and one side band above the supply frequency which is called upper-side band (USB).
Even though thermal and vibration monitoring have been utilized for decades, most of the recent researches have been directed towards electrical monitoring of the motor with emphasis on inspecting the stator current of the motor.
The MCSA method was utilized for diagnosis of the motor and inverter defects using information from the motor stator current. In majority of applications, the stator current of an induction motor is easily obtainable because it is utilized in the protection of the motors from over-currents, ground currents. Thus, for the condition monitoring and fault diagnosis via MCSA, no extra sensors are required. It is a non-invasive method as it does not require direct access to the motor for its implementation [25, 52–58]. Thus, MCSA for the condition monitoring of the induction motors finds its application majorly in nuclear power plants, offshore pumping stations and defence industry where access to the motor is not possible.
Due to its non-invasive feature, MCSA has received the attention of many researchers and intensive research has been conducted on the MCSA. Initial efforts in MCSA can be credited to Schoen et al. [25, 53, 54]. They present a method to diagnose the motor faults based on the spectral analysis of stator current signal. Artificial neural networks were trained to learn the characteristic defect frequencies in current spectrum for the online fault diagnosis. The detection algorithm was implemented on a custom-designed test rig and its performance was verified on various fault types. Benbouzid et al. [55–57] addressed the application of MCSA for the diagnosis and localization of electrical and mechanical faults of induction motors. The initial steps taken to investigate the efficiency of MCSA for the purpose of motor fault diagnostic were discussed. Experimental results clearly illustrate the stator current spectral analysis sensitivity to induction motor faults. Later, Duque et al. [58] validated the bearing fault detection capability of MCSA on inverter-fed induction motor. In the current spectrum analysis of the motor, running values are compared with baseline values. In real time applications, baseline values are dependent on the operating conditions. To tackle this issue, Stack et al. [59] proposed new method which keeps track on baseline data at various operating conditions of the motor. They used different load conditions and for each case they compare the baseline values with running values to estimate the health condition of the motor. Along with the FFT method for the analysis of the spectrum, they used some advance signal processing and pattern recognition techniques for defecting analysis of the motor. An assessment of monitoring methods used for detection of bearing localized faults of induction motors was presented by Refs. [38, 60–62]. They proposed stator current monitoring as a very applicable technique in an industrial environment. Their research presented the current spectrum analyses along with noise cancellation method to detect mechanical faults of a variety of motors. They also propose a new method to damage the bearings via shaft current. The interpretation of the spectrum of the motor current indicates that this technique can successfully diagnose the bearing localized defects.
An improved stator current-based monitoring scheme was reported in Ref. [63], which perfectly blends Fourier transform, self-adaptive filter and rotor slot harmonics-based slip estimation techniques together. The experimental results on the bearing outer race localized defects demonstrate that the presented scheme is effective. In order to diagnose the incipient faults in rotor bars, a bilinear time-frequency analysis of stator current along with adaptive filter technology was performed by Boqiang et al. [64]. The results indicate that the proposed method has the capability to diagnose broken rotor bar faults at their incipient stages. Application of MCSA for the detection of artificially damaged rolling bearings in asynchronous machine was confirmed by Trajin et al. [65]. Blodt et al. [66] and Terra et al. [67] utilized the stator current analysis and vibration analysis techniques to detect bearing localized defects. They also proposed a new model for the investigation of the effect of load torque variations on the stator current spectrum. The experimental results indicated that oscillations of the torque produce the varying frequency contents which can be observed in the stator current spectrum. Bayindir et al. [68] and Ioannides et al. [69] presented an automated fault detection system for the induction motors based on programmable logic controllers. They used the speed sensor, temperature sensor and current sensor to measure the motor speed, motor temperature and running current. The system was developed to automatic turn-off the motor if any one of the measured variable exceeds the preset values. However, the proposed condition monitoring system proves to be very expensive due to involvement of the sensors.
A novel method for the use of the stator current and efficiency of the motors as pointer of rolling-bearing defects was proposed by Frosini et al. [70, 71]. Their work describes the experimental results of bearing localized faults in outer and inner race of bearings. The analysis of the reduction in the efficiency of the motor due to defected bearings was also reported. Ebrahimi et al. [72] investigated the efficiency of the MCSA for the detection of stator faults in permanent-magnet synchronous motors. Experimental results indicate that the introduced method can detect the short-circuit fault incisively. Mehala [73] used the MCSA scheme to identify the bearing localized defects. FFT spectrum of the motor stator current was obtained and analysed. Experiments were conducted on the two defect levels (hole sizes 2 and 4 mm) in outer and inner race of the bearing under no-load and full-load conditions. The results obtained through the experiments indicate that under no-load condition, the change in amplitude values at characteristic defect frequencies is very small (<5 dB) however for full-load conditions, the change in amplitude is detectable (>5 dB to <8 dB). Along with FFT analysis of stator current, the researcher also performs wavelet and Park vector analysis of stator current for diagnosis of various motor faults.
A novel method was proposed by Romero et al. [74] which merged information entropy analysis with fuzzy logic inference to diagnose and classify faults like broken rotor bars, bearing malfunctions, stator unbalance and combinations of faults by analysing stator current signal. The proposed method shows satisfactory results that prove its suitability for online detection of single and multiple faults in an automatic way through its hardware implementation. Seera et al. [75] presented a novel approach to detect and classify comprehensive fault conditions of induction motors using a hybrid fuzzy min–max (FMM) neural network and classification and regression tree (CART). MCSA method was applied to form a database comprising stator current signatures under different motor operating conditions. Comparison of stator current analysis via FFT and wavelet transform was shown in Ref. [76]. Experimental results indicates that stator current analysis via FFT can diagnose bearing localized defects only under steady state conditions, while, it is unable to diagnose the faults when motor is operating in transient condition. However, stator current analysis via wavelet transform has the capability to diagnose the faults under steady state and transient operating conditions of the motor. Recently, a stand-alone multi-sensor wireless system for continuous condition monitoring of induction motors has been proposed by Ref. [77]. The proposed wireless system provides a low-cost alternative to an expensive condition monitoring technology available through data acquisition equipment.
In a recent study, the fault frequencies inside the stator current spectrum were analysed through iterative method which provides an efficient fault diagnosis in the non-linear motor operations [78]. The winding function approach was used by Ref. [79] to diagnose rotor faults. The theoretical derivations were validated with experimental results. To enhance the reliability of the fault diagnosis system, Choi et al. [80] proposed a condition monitoring scheme which is based on speed feedback error management. In Ref. [81] a cross-correlation-based condition monitoring system was used to diagnose the induction motor eccentricity faults. The validity of the proposed method was confirmed through real time experiments performed on digital signal processing (DSP)-based motor drive. In a recent paper, Aydin et al. [82] proposed a hybrid approach based on multiple wireless sensor systems for fault diagnosis of induction motors. The proposed method was shown to be useful for analysing and monitoring signals from multiple induction motors. A novel analytical model based on stator current monitoring was developed by Blodt et al. [83] for the analysis of bearing defects. The results obtained through spectral analysis of the measured quantities validate the proposed theoretical approach. Stack et al. [84] presented various techniques to simulate artificial defects in the bearings of induction motor. Motor asymmetrical fault signatures were identified by Benbouzid et al. [85] through spectral analysis of motor current signal. An envelope analysis of the vibration signal was used to diagnose bearings localized defects [86]. The results achieved with proposed technique are shown to be strong function of selection signal bandwidth [86]. A wavelet-based condition monitoring system using analysis of the acoustic emission signal was proposed by Kang et al. [87]. A generalized fault analysis system in multi-phase machines was proposed by Choi et al. [88].The fault diagnosing capability of the proposed scheme has been verified mathematically through simulations. Wang et al. [89] has used an improved combination of the Hilbert and wavelet transforms to analyse the incipient bearing localized defects. Experimental results indicate that the extraction capability of bearing localized fault frequencies is greatly enhanced by the proposed method. An intelligent fault diagnosis scheme based on an independent component analysis was presented by Widodo et al. [90]. An integrated system for motor bearing fault identification is presented in Ref. [91]. Hwang et al. [91] proposed an integrated fault diagnosis system based on cepstrum coefficient method for feature extraction from motor vibration signals. The experimental results indicate the effectiveness of cepstrum in diagnosing the bearing health. Neural networks models with a decision structure are presented in Ref. [92] to analyse the bearing localized defects. The results show good performance of the implemented model and its ability to identify the bearing localized faults.
Gears are the main part of an electromechanical power transmission system in majority of industrial applications [93]. Unexpected failures can be prevented through detection of incipient gear faults. This will also help to reduce machine down-time and minimize financial consequences of gear damages. This cannot be realized without using an efficient fault diagnosis and condition monitoring system [94]. Although vibration analysis has been shown to be the reliable method for gear fault detection but the sensitivity to the installation position and the background noise due to external mechanical excitations are main drawbacks of the vibration measurement for gear and researchers are constantly looking to have non-invasive method for gear fault diagnosis [95, 96]. The gear fault detection using non-invasive method offers great advantages over invasive techniques principally due to its effective cost and the need of minimum changes in the system installation. In this context, an extensive research has been performed during recent years for the gear fault diagnosis using non-invasive techniques, example, using current and voltage measurements in the vicinity of motor drive systems [97–101].
As related to this, Blodt et al. [102] examined the detection of mechanical fault-related load torque oscillations in induction motors using a stator current monitoring. They developed a theoretical model to show the link between torque oscillation and modulation of a stator current component. However, they neglect the impact of the gear stiffness on the stator current. The effect of gearbox characteristic frequencies in the stator current of induction machine was studied by Ref. [95]. It was shown that the input shaft, layer shaft and output shaft frequencies in a multi-stage gearbox appear in the electromagnetic torque spectrum. Also, these harmonics appear as the sideband frequencies around the electric supply frequency of the stator current. The mesh frequencies were also well identified in the measured stator current. Their experimental investigation indicates that magnitudes of some rotation and mesh related frequencies are sensitive to the gear tooth fault [95, 103, 104]. A more rigorous attempt was carried out by Kia et al. [105, 106] to analyse the impact of motor coupled gear on the stator current spectrum. Their theoretical and experimental investigations indicate that harmonics appeared in motor current spectrum at mesh frequencies and mesh-related frequencies for healthy gears. For defected gear, additional harmonics related to fault-induced mechanical impacts are produced at the rotational frequency. The experimental results indicate that mesh and mesh-related frequencies have very weak signatures and are suppressed in the noise. The diagnosis of damaged tooth of the gear through MCSA at motor full-load conditions was reported in Refs. [107–109]. They also presented the comparison of diagnosis capabilities of vibration, acoustics and stator current analysis techniques. Stator current has been shown to be the suitable non-invasive method to diagnose gear faults. A simplified dynamic model considering a realistic behaviour of gear with minimum number of gear mechanical parameters was used to study the effect of gear torsional vibrations on motor current spectrum [110–112]. The impact of transmission error in gear was shown to be related to pinion and wheel eccentricities and tooth profile abnormalities which produces pinion and wheel rotation sidebands around the fundamental and mesh frequencies.
An attempt has been performed by Ottewill et al. [113] to diagnose the tooth pitting fault in a multi-stage gear. They have used a low-degree of freedom model for gear dynamic model. It was verified by Girsang et al. [114] that the gear teeth faults may generate mechanical impacts which can be observed in the torque and hence in machine electrical signatures. In Ref. [115], Huh et al. focused on extracting operating point independent fault signatures by using a kinematic error observer, spatial domain sampling methods and spatial domain signal filtering methods for gear fault diagnostics of electromechanical actuators. Bogiatzidis et al. [116] reported the identification of mechanical vibrations due to backlash phenomena appearing between the pinion gear and the girth gear rim of the kiln is realized using the MCSA. The proposed diagnostic method was tested on under-scale laboratory test rig. It was shown that due to fault in pinion gear, the pinion rotation frequencies appear around fundamental supply frequency.
An online gear fault diagnosis system was reported in Refs. [108, 117] using a non-invasive stator current space vector analysis. The proposed algorithm is based on the computation of the fault index by using fault-related frequencies in the current space vector instantaneous frequency spectrum. Tests performed with different load levels demonstrate a possible online condition monitoring and fault diagnosis of gear tooth surface damage fault detection. It has been demonstrated that incipient faults in gears produce small fault signatures that are sometimes buried in environment noise and thus could not be reliably detected through MCSA. Recently, a statistical tool called spectral kurtosis with reference has been proposed to define the electromechanical system healthy state reference. This technique proves its effectiveness in case of load torque oscillation fault only [118].
Although MCSA has the capability to diagnose gear defects and bearing localized defects, however, very small change in amplitude occurs at characteristic defect frequencies under no-load condition. Also in an arbitrary noise condition, the small fault signatures are buried in noise and it is difficult to discriminate between change in amplitude value due to fault and random noise [38, 53–72]. Another disadvantage of the MCSA is that sometimes two side band components (LSB and USB) lie near to the fundamental component and amplitude of the side band components is suppressed by the highest peak at fundamental component. This can create misdetection in an online fault diagnosis system [107–118].
Since bearings are used to support the rotor during rotation, hence any defect in bearing will affect the radial movement of rotor. Due to this radial movement, air-gap between rotor and stator will change to cause magnetic flux variations. These flux variations create modulations (oscillations) in the instantaneous power which could be observed as two sideband components, at (2fe – fv), (2fe + fv), and one fault component appears directly at the vibration frequency (fv). The location of these harmonic frequencies allows the identification of abnormalities in the bearing.
The instantaneous power analysis (IPA) method has been used by several researchers to detect rotor and eccentricity defects. Ahmad [119] uses the motor current, voltage, flux and IPA methods to investigate the broken rotor bars and eccentricity defects of the motor. His study shows that although the rotor bars and eccentricity defect of the motor can be detected through current, voltage and flux analysis, however, these techniques are not effective under no-load conditions of the motor. On the other hand, the instantaneous power analysis scheme diagnosis the rotor and eccentricity defects effectively even under no-load condition of the motor. This is due to the reason that the motor power is the product of the supply voltage and current so it contains more information than the current and voltage only. In later work, the superiority of the IPA method over MCSA was confirmed in [120–123] for the diagnosis of faults in rotor, stator and eccentricity.
The comparison of the MCSA and IPA for 2 mm bearing outer race defect is shown in Figures 12 and 13, respectively. It has been observed from Figures 12 and 13 that the MCSA is not suitable for detection of defects at lower load levels because very small change in the amplitude value (2 dB) appears at characteristic defect frequencies of 28 and 128 Hz in stator current spectrum. However, comparatively large change in amplitude value (7 dB) appears at characteristic defect frequencies of 21, 79 and 179 Hz in instantaneous power spectrum. Also, it has been observed that the IPA carries an additional characteristic frequency component that provides an extra piece of information that can be utilized in a reliable intelligent condition monitoring system. Thus, IPA has more capability to detect bearing defects at low-load conditions as compared to MCSA.
The stator current spectrum under no-load conditions of the motor (a) healthy motor and (b) defected bearing with 2 mm outer race defect.
Instantaneous power spectrum under no-load conditions of the motor (a) healthy motor and (b) defected bearing with 2 mm outer race defect.
Incipient defects are defined as slowly developing defects or small unpredictable variations in the system. They are characterized by small amplitude compared to the useful signal. Considering the definition of incipient defects, as a slowly developing defect, it is important to address the issue of detecting these defects at the earliest possible stage meaning smallest amplitude (smallest severity). It has been observed that the low energy harmonics are produced due to incipient bearing localized faults and stator current analysis technique proves to be less efficient to detect low energy fault signatures especially under noisy environment. The IPA method has the ability to detect low energy fault signatures but in an online testing system it is difficult to discriminate the amplitude changes due to environment noise and due to existence of the fault. Therefore, it is unlikely to make decisions without considering the noise variations. As related to this, in an online fault diagnosis system the environmental noise modelling has been a practical issue and many studies have been performed to deal with it.
The averaging of multiple spectrums of stator current was used to eliminate the noise disturbances [124]. Recently, in Ref. [125], Wiener filter is used to eliminate all signatures that are irrelevant to the motor fault signatures. To achieve the high performance of the condition monitoring system, a statistical process control (SPC) is used [63]. Golafshan et al. [126, 127] presented the Singular Value Decomposition (SVD) and Hankel matrix-based de-noising process for the elimination of the background noise and the improvement in the reliability of the fault detection process. However, the proposed method is proven to be computationally intensive. A classical multiple signal classification method has been proposed by Kia et al. [128] to suppress the noise during the fault diagnosis of the motor. However, the proposed method takes long computation time to find fault signatures and is affected by the low signal-to-noise ratio. To solve this problem, an algorithm that is based on zooming in a specific frequency range of the FFT spectrum was proposed in [129]. Kim et al. [130] proposed the idea for separating rotor faults and load oscillations to reduce the false alarm rates in an online fault diagnosis system. It was reported in Ref. [131] that Wigner–Ville spectrum analysis based on cyclic spectral density (CSWVS) was able to separate the bearing fault patterns from random noise in the vibration signal. As compared with the envelope analysis for rolling element bearing diagnosis, the strongest element of CSWVS may be its diagnostic ability for bearing with distributed faults. In the experimental study, the results of envelope analysis, no matter what filtering techniques are used, fail to extract bearing fault features and might be misinterpreted as a gear fault. However, CSWVS utilizes the second order cyclo-stationary property of the vibration signals produced by bearing distributed fault, and clearly extracts its fault features reducing the masking effect of additive stationary noise. Wang et al. [132] addressed challenging issues on de-noising and identification of the incipient fault deterioration grade from the noisy vibration signal for aircraft engine rotor prognostics. The enhanced robust methods include an adaptive wavelet de-noising technique for weak signature enhancement and correlation dimension for performance degradation assessment. The experimental results verified that the weak vibration signal features of rotor are successfully revealed and enhanced using adaptive wavelet de-noising method, and correlation well identify the rotor rub-impact fault deterioration grade.
Eccentricity faults in induction motor were analysed by Refs. [133, 134] using a cross-correlation method. The pre-determined threshold levels that have been used are as follows: amplitude less than –60 dB healthy motor, amplitude –60 dB to –40 dB tolerable defects and amplitude higher than –40 dB severe defects. A statistically derived adaptive threshold definition was proposed by Toliyat et al. [135]. The experimental results confirm the validity of the proposed approach to diagnose eccentricity and rotor fault at 70% loading condition of the motor. Although, the proposed approach considers the noise variations in real time applications; however, the performance of the proposed approach was not tested under variable operating points of the motor. In a similar work, Rajagopalan et al. [136] use an adaptive threshold scheme based on percentage of the fundamental current signal. The advanced signal processing algorithms are used to diagnose fault signatures [137]. In this study, the threshold is pre-determined based on prior tests before the diagnostic procedure starts. Although, the statistical performances of the instantaneous noise and bias with respect to motor operating points are not provided in that study but the suggested solutions present an intuitive way to design a performance oriented adaptive threshold scheme for an online fault diagnosis system. An analytical model to detect the incipient faults in the plant process in presence of an arbitrary noise was recently presented in Refs. [138–141]. Their modelled threshold scheme that is based on the probability distribution function has shown higher efficiency for incipient fault detection in noisy environment.
Notably, the pre-determined threshold schemes for reliable diagnosis of electrical faults in induction motor faults using MCSA presented in Refs. [133–137] could be used to estimate the fault severity, but these threshold schemes tend to detect sufficiently strong fault signatures to avoid noise interference. Thus the scheme could not be used to diagnose small fault signatures associated to motor mechanical faults under no-load conditions.
Fournier et al. [142] defined the threshold references in healthy condition of the motor based on the statistical spectral kurtosis measurements. The threshold scheme produces efficient results at specific speed and load levels of the motor. However, this threshold scheme does not consider instantaneous noise variations with respect to motor operating point (load, speed), so errors in the detection occur when operating point of the motor changes. Picot et al. [143] proposed a threshold scheme for the detection of small fault signatures related to bearing cage defects in permanent magnet synchronous motor (PMSM). The noise variance of the measured motor current spectrum was minimized by integration process and threshold was designed by calculating mean and standard deviation of the frequency bins. Although, the proposed method was shown to produce good performance at various speeds (variable supply frequency) of the PMSM, however, it has some limitations. Firstly, the performance of their designed threshold was not measured at various load conditions. Secondly, the designed threshold scheme is dependent on the sampling size and window size. The large window size may attenuate the amplitude of bearing fault signatures. The impact of noise variations with respect to load variations on the reliable decision making of the existence of small fault signatures needs to be investigated. Notably, this work provides intuitive way towards the design of performance-based decision making system independent of environment impacts and motor operating points.
Limitations of the existing non-invasive fault diagnosis techniques considering environment impacts are described in Table 1.
Reference | Fault type | Threshold design technique | Limitations |
---|---|---|---|
[133, 134] 2008, 2011 | Eccentricity | Pre-determined threshold |
|
[135] 2012 | Eccentricity, Rotor | Statistically derived threshold |
|
[136] 2006 | Eccentricity | Pre-determined threshold |
|
[137] 2006 | Bearing, Rotor | Zero input test-based statistical analysis |
|
[142] 2013 | Unbalance | Reference-based statistical analysis (spectral kurtosis) |
|
[143] 2014 | Bearing cage Defect | Reference-based statistical analysis (mean and standard deviation) |
|
Limitations of previously used MCSA-based fault diagnosis techniques considering environment impacts.
Park vector analysis (PVA) of motor current which is mainly used for field oriented control of induction motor has received a growing attention in the recent years in condition monitoring applications. Few researchers have used PVA with emphasis on the bearing localized faults, rotor faults, eccentricity faults and stator faults [144–147]. In Park’s transformation process, the three balanced AC quantities (Ia, Ib, Ic) are reduced to two DC quantities (Id, Iq). In analysis of three-phase synchronous machines, Park’s transformation transfers three-phase stator and rotor quantities into a single rotating reference frame to eliminate the effect of time varying inductances [144, 145].
The Park vectors under ideal conditions of the motor represent a circular pattern centred at the origin. However, the shape of the circle changes in presence of the faults inside the motor and the various types of faults generate various types of shapes. Thus by detection of various patterns, one can analyse the type of fault inside the motor. The Park’s transform is a graphical method to analyse the status of motor and does not require analytical expressions to calculate any specific defect frequency.
Zarie et al. [144] performed experiments on induction motor to diagnose bearing localized and extended defects (multiple holes in inner or outer race). Classification of the various faults was achieved through utilization of neural networks. It was concluded in their study that the proposed method provides a powerful and general approach to incipient fault detection. Spyropoulos et al. [145], Laughman et al. [146] and Parra et al. [148] reported that impact of the motor stator related faults could be examined through the Park vector transformation approach. It was claimed that by using this approach, effects of stator faults can be differentiated from time-varying loads. Salem et al. [147] measure the thickness of Park vector curve using curve splitting factor. The experimental results on bearing outer race defect indicate that thickness of the Park vector curve increases due to fault. Rezig et al. [149] and Salem et al. [150, 151] conducted experimental study to diagnose the bearing localized defects and eccentricity faults through Park vector transform of motor stator current. Experimental results indicate that Park vector transform method can detect the occurrence of faults but unable to identify the fault locations. In a recent study, Kuruppu et al. 152] demonstrated that Park vector analysis method has capability to diagnose stator inter-turn faults in inverter-fed field-oriented control motors. Proof of accurate fault detection capability for a wide speed range is presented through simulation and experimental results.
The example of Park vector analysis of stator current for bearing localized defects is shown in Figure 14. It can be observed from Figure 14 that bearing localized defects cause an increase in thickness of the Id, Iq curves. The increase in curve thickness is due to the harmonics induced by the localized defects inside the bearing of the motor. Therefore the analysis of the Id, Iq curves can be a useful means for the fault diagnosis of induction motors.
Example of Park vector analysis of stator current for (a) healthy bearing, (b) outer race localized defect and (c) inner race localized defect.
Most of the published work on the bearing condition monitoring via non-invasive techniques as discussed in focused on diagnosis of bearing localized defects. It is based on some characteristic fault frequencies that appear in spectrum of the stator current or instantaneous power. However, the absence of clear characteristic fault frequencies should not be interpreted as a completely healthy condition of the bearing. On the other hand, the bearing distributed faults produce unpredictable broadband effects which are not necessarily related with specific fault frequencies. These faults are common in industry, while they are often neglected in the research literature.
Time-domain analysis is a useful feature extraction tool for condition monitoring and fault diagnosis of electrical motors. Time domain averaging (TDA) is a traditional and typical method to detect fault signals in electrical motors. It extracts a periodic component of interest from a noisy compound signal. Data-clustering techniques are used to extract an average pattern that serves as the mechanical imbalance indicator. Zhang et al. [153] proposed the idea of creating artificial distributed defects in bearings of induction motor via externally applied shaft current. This idea was important as the defects would be sorted according to the kind of signatures generated by defects instead of where the defects were located physically. Most of the condition monitoring approaches concerning fault detection found in the literature have been mainly focused on identifying single-point defects. Indeed this class of defects is quite important, however, an approach that is comprehensive and robust must have the capability of detecting not only single-point defect but also distributed defects in the bearing. The data obtained from 10 bearings failed by their proposed method, was analysed in time domain. It was shown that drastic variations in machine vibration and stator current occur in case of defected bearings. A method to segregate the bearing localized and distributed defects based on the time domain analysis of vibration, stator current and acoustic emission signals was presented by Navarro et al. [154]. The RMS values of the multi-sensory signal for healthy bearing, bearing localized and distributed defects were collected and faults were classified based on fuzzy inference analysis. In Refs. [155, 156], it was reported that generalized roughness in bearings of the motor produces a frequency spreading of the characteristic fault frequencies, thus making it difficult to detect with MCSA method. In the papers, it was proposed to use a statistical analysis of typical bearing faults in order to identify the spreading bandwidth related to bearing surface roughness faults, relying on current and vibration measurements only. A diagnostic index based on computation of energy in the previously defined bandwidth was used to diagnose bearing surface roughness faults. The proposed method was validated experimentally with vibration and current signals, with robust and reliable results. However, implementation of their proposed method needs computational efforts and implementation of this method for inner and outer race surface roughness was not given. In a recent study, Dalvand et al. [157] analyse bearing distributed defects in inner and outer race of bearing simultaneously. They use statistical analysis of the instantaneous frequency of motor voltage space vector (MVSV) and vibration signal. The statistical indices like mean value (M), RMS value, standard deviation (SD), global kurtosis (GK), skew factor (SF) and crest factor (CF) were utilized to analyse the measured signal. It was shown that mean value and RMS are not proper indices to analyse the distributed defects in bearings because the values of these indices for healthy and defected bearings are not significantly different. However, the GK, SF and CF are proper indices to diagnose bearing distributed faults. Experimental results indicate that although the statistical time domain analysis of MVSV and vibration signals have capability to diagnose the bearing distributed defects; however the reliability of MVSV is better than vibration monitoring. The analysis of individual defect in bearing elements was not presented in their study.
The literature review has shown that the invasive methods like vibration analysis, acoustic emission, noise analysis, chemical analysis and temperature measurements were applied to protect motors from various faults. However, sensors used in these methods are very expensive. Another disadvantage of these methods is that they require access to machine for sensor installation which is not possible in every application. Also it requires special expertise for the proper installation of sensors on the machine for accurate results. Therefore sensor-based condition monitoring methods are not reliable.
Review papers presented in Refs. [158–163] on the condition monitoring techniques for the induction motors demonstrate that extensive research has been carried out in the last decade on the development of a non-invasive condition monitoring system for diagnosis of gear defects and bearing localized faults. It has been found that the mechanical vibration produce characteristic frequencies in stator current spectrum. The magnitude of the specific characteristic frequencies increases with the increase of vibration. Every type of the motor defect has its own unique characteristic defect frequencies. The MCSA has been extensively used to find out these frequency modulations.
The implementation of MCSA for motor condition monitoring is not so complex. However, low amplitude fault signatures are induced due to incipient faults under no-load condition and thus could not be reliably diagnosed through MCSA. Recent developments in non-invasive condition monitoring scheme demonstrate that PVA of motor stator current has the capability to diagnose the motor faults at incipient stages. It was shown that the proposed method would give good analysis of machine faults even if accurate fault frequency information is unavailable. In recent years, IPA method to diagnose rotor, stator and eccentricity faults at incipient stages conditions was proposed by few researchers. However, applicability of the IPA for mechanical fault diagnosis in induction motor has not been reported in literature [164–170].
The incipient defect diagnosis in the machinery with unknown distribution of measured signals and unknown changed parameters is an important issue. However, most of the fault diagnosis techniques need a priori knowledge on the signal distribution, changed parameters and the changed amplitude. Fault detection plays a key role in enhancing today’s technological system’s high demands for performance, productivity and security. The sensitivity of the condition monitoring and fault diagnosis methods depends on the application of main goals. When productivity is the main goal then the sensitivity requirement of condition monitoring and fault diagnosis system is weak and only large defects should be detected. However, when security is the main goal, undetected defects even with very small severity assessment may result in catastrophic growing failures. For online fault diagnosis, when safety is the main priority, it is crucial to be able to diagnose incipient faults in presence of environment noise. Although IPA has some implementation advantages over MCSA for incipient fault detection but the signatures of IPA are affected by industrial noise perturbations. There is much scope for research to improve the capabilities of IPA in reliable online fault diagnosis in an arbitrary environment noise.
Notably, the substantial number of research studies has been found focusing into detection of bearing localized faults via non-invasive condition monitoring methods. Nonetheless, bearing distributed defects does not produce localized defect frequencies and thus could not be analysed via these methods. Recently, few studies have been found focusing on time domain analysis of stator current signal and extracting the features like RMS and kurtosis values. However, complexity involved in time domain analysis of stator current signal is the major drawback. As PVA performs the graphical analysis of stator current and does not require frequency information for fault detection thus its capability to diagnose bearing distributed defects should be further researched.
The advantages and drawbacks of the existing non-invasive condition monitoring methods are presented in Table 2.
No | CM technique | Advantages | Drawbacks | Reference |
---|---|---|---|---|
1. | MCSA |
|
| [25, 38, 52–73] |
2. | PVA |
| Further investigation required to test its capability for bearing distributed defects | [144–152, 171] |
3. | IPA |
|
| [119–123] |
Advantages and drawbacks of non-invasive condition monitoring methods.
Based on the findings, there are further problems to be considered both in the development of the technique and in the experimental design. These include
Development of non-invasive condition monitoring scheme to diagnose faults in an arbitrary environment noise conditions
The non-invasive IPA has shown some implementation advantages over MCSA to reliably diagnose mechanical faults. However, small fault signatures under low load conditions are buried in noise and it is difficult to discriminate amplitude changes due to fault and due to noise. Thus, there is a need to develop a robust non-invasive condition monitoring scheme to make reliable decisions on the existence of fault signatures.
Development of non-invasive condition monitoring scheme to diagnose bearing distributed faults
Most of the published work on the bearing condition monitoring via non-invasive techniques is focused on diagnosis of bearing localized defects. It is based on the some characteristic fault frequencies that appear in spectrum of the stator current or instantaneous power. Nonetheless, bearing distributed defects does not produce characteristic defect frequencies and thus could not been analysed via MCSA or IPA. These faults are common in industry, while they are often neglected in the research literature. As PVA performs the graphical analysis of stator current and does not require characteristic defect frequencies information for fault detection thus its capability to diagnose bearing distributed defects should be further researched.
Development of hand-held instrument for on-site machine condition monitoring
The IPA and PVA algorithms could be embedded to develop a hand-held instrument for on-site condition monitoring of induction motors. This will help to reduce the installation cost of the data acquisition system especially for small and medium scale industrial use.
Reliability tests for mainstream industries
The developed IPA and PVA algorithms should be expanded and utilized to analyse faults in turbines and generators. For consideration to be acceptable by the main stream industries, a reliability test of the developed algorithms should be conducted on large size motors (more than 40 HP).
Multiple bearing faults analysis
Even though the two techniques as proposed i.e. the instantaneous power analysis and Park vector analysis can monitor the conditions of induction motors from various scenarios, however these are not sufficient for most applications because outcomes of the analysis are based on the assumptions that each fault occurs independently. The extension of the approach as proposed in this work, to understand how each approach reacts to a combination of several faults (e.g. stator, rotor, eccentricity, bearings, etc.), would be useful.
The ability to forecast motor faults at incipient stages is vital to reducing maintenance costs, operation down-time and safety hazards. This paper synthesized the progress in the research and development in condition monitoring and fault diagnosis of induction motors. The review presented in this paper has contributed to an improved understanding of the development of practical non-invasive condition monitoring and diagnostic tool for induction motors. The non-invasive methods, namely MCSA, PVA and IPA overcome the disadvantages associated to invasive methods. The MCSA, PVA and IPA can successfully diagnose the gear and bearing localized defects. However, further research is required to analyse bearing distributed faults via non-invasive condition monitoring methods. It has been observed that IPA has some implementation advantages over MCSA for incipient fault detection but IPA can be affected by environment noise perturbations. There is much scope for research to improve the capabilities of IPA in reliable online fault diagnosis system operating in an arbitrary environment noise. Furthermore, to realize the greatest economic and implementation benefits of IPA and PVA, it is important to design a hand-held condition monitoring system based on IPA and PVA techniques by considering the asset management perspective.
The authors acknowledge the support from Universiti Teknologi PETRONAS for providing Universiti Research Innovation Fund (URIF) and the Ministry of Higher Education (MOHE) Malaysia for the award of the Prototype Research Grant Scheme (PRGS).
Pandemics and epidemics of infectious origin are large-scale outbreaks that can greatly increase morbidity and mortality globally or over a wide geographic area, respectively [1]. Pandemics have occurred throughout history and appear to be increasing in frequency in the last centuries. Noteworthy examples include the Black Death at the end of the Middle Ages, Spanish flu in 1918, the 2014 West Africa Ebola epidemic or the current COVID-19 pandemic. The direct impact of pandemics on health can be dramatic. These large outbreaks can disproportionally affect younger or active workers, but vulnerable populations such as the elderly are at a particular high-risk. Pandemics can cause acute, short-term as well as longer-term damage to economic growth due to public health efforts, health system expenditures, and aid to affected sectors. Evidence suggests that epidemics and pandemics can have significant social and political consequences too, by debilitating institutions, amplifying political tensions, stigmatizing minority populations, or encouraging sharp differences between social classes [2].
Outbreaks by respiratory ribonucleic acid (RNA) viruses such as influenza or coronaviruses entail the principal threat due to their ease of spreading among humans, their potential severity and recurrence. However, other RNA viruses such as flaviviruses (Zika) or filoviruses (Ebola) must be taken into consideration due to a great overall burden of morbidity and mortality [3]. Antiviral drugs can help mitigate a viral outbreak by reducing the disease in infected patients or their infectiousness. While these drugs can be very successful against some viruses (e.g. hepatitis C virus [HCV]) [4], they are not universally effective as exemplified in the current SARS-CoV-2 pandemic [5]. Nowadays, having effective vaccines may be the only tool to reduce susceptibility to infection and thus, prevent the rate of virus spread [2].
Vaccination has dramatically decreased the burden of infectious diseases. Vaccines have saved hundreds of millions of lives over the years [6]. It has been estimated that approximately 103 million cases of childhood diseases were prevented in the United States through vaccination between 1924 and 2010 [7]. The eradication of smallpox in 1980 through vaccination is considered one of the crown accomplishments of medicine. Despite these achievements, effective vaccines have been developed against just over 30 pathogens among bacteria and viruses. There are many pathogens, including viruses such as human immunodeficiency virus (HIV) or respiratory syncytial virus (RSV), for which all efforts for vaccine development have failed so far. In addition, current available vaccines for worldwide important viral diseases like influenza are suboptimal, especially in the elderly, resulting in vulnerability among billions of at-risk populations [6]. On the other hand, having a new effective and safe vaccine in time to control highly contagious emerging viruses that cause epidemic or pandemic threats is an almost impossible task considering the timeframes for vaccine development. This includes preclinical and clinical research, its approval by the regulatory authorities, as well as its production and distribution [3].
Altogether, it has been postulated that one possibility of filling the gap between the appearance of a viral outbreak by an emerging pathogen and the availability of a specific vaccine is to take advantage of the heterologous protection of some existing vaccines, in order to increase the non-specific resistance of the host through trained immunity [8, 9].
Conventional (specific) anti-infectious vaccines are biological preparations containing live-attenuated or dead microorganisms, their antigens or nucleic acids encoding for them, designed for specific pathogens. The purpose of vaccination is to induce a long lasting adaptive immune response against key antigens able to confer host resistance for future encounters with the corresponding pathogen. Either the production of antibodies, generation of T helper/effector cells, or both, may play a critical role in such a resistance, which greatly depends on the type of pathogen, the route of entrance and the host-pathogen relationship (e.g., extracellular and/or intracellular) [10]. Successful vaccines are highly effective not only in inducing long-lasting immunity against disease-causing pathogens, but also in providing herd immunity to the community that substantially restricts the spread of infection [6].
Most of the vaccines available today have been developed empirically and used successfully long before their mechanism of action on the immune system was understood. Early protection is associated to induction of antigen-specific antibodies, being their quality (avidity, specificity, or neutralizing capacity) key factors for their efficacy. Long-term protection relies on the persistence of vaccine antibodies and availability of immune memory cells capable of rapid and effective reactivation with subsequent microbial exposure. On the other hand, T cells have a critical role in the induction of high affinity antibodies and immune memory. Furthermore, T cells have a direct role in protection conferred by some vaccines, including the tuberculosis Bacille Calmette-Guérin (BCG) vaccine [11].
Vaccines using whole pathogens have been classically classified as either live attenuated or inactivated (killed). Subunit vaccines contain just selected antigens (e.g., proteins, polysaccharides). Recently, due to a growing availability of bioinformatics and sequencing tools, there has been an increase interest on so-called “rational” vaccine design approaches for subunit vaccines, such as the reverse vaccinology [12]. In this regard, modern vaccines include recombinant proteins or nucleic acids [13]. Rather than administering the antigen itself, DNA and mRNA vaccines targeting dendritic cells (DCs) encode the antigen of interest that will be produced by the vaccinated host, representing a new era in vaccinology [14]. In fact, the first RNA vaccine licensed for humans in Western countries has been recently developed for SARS-CoV-2.
As commented before, a vaccine response is linked to the induction of T and B cell specific responses to the antigens contained in the vaccine. This requires lymphocyte activation, proliferation and differentiation on specialized lymphoid tissues (e.g lymph nodes), where antigen presenting cells, like DCs for T cells or follicular dendritic cells (FDCs) for B cells, are present. Mature DCs are recruited into the T cell areas of lymph nodes from the periphery, e.g., at the site of injection of the vaccine. DCs express pattern recognition receptors (PRR) that recognize evolutionary conserved pathogen-associated molecular patterns (PAMPs) that are not contained in self-antigens and are identified as “danger signals” [15]. When immature DCs are exposed to the vaccine-derived antigens at the site of vaccination, they uptake them and become activated [16]. This activation will lead to their maturation with the expression of homing receptors at their surface, triggering DC migration to the draining lymph node through afferent lymphatic vessels, where the activation of T and B lymphocytes will occur. Mature DCs process the up-taken antigens and present them to naïve T cells associated to molecules of the major histocompatibility complex (MHC) within the T cell areas of lymph nodes. On the other hand, unprocessed native antigens, either free or complexed with antibodies or complement, access the B cell areas of lymph nodes (lymphoid follicles) where they are captured by FDCs and displayed from their cell surface to the B cells. Antigen-specific B cells will rapidly proliferate forming a germinal center and differentiate into plasma cells producing low-affinity immunoglobulin (Ig) M antibodies. The B cells will then receive additional signals from activated T cells, undergoing isotype antibody switch from IgM to IgG or IgA and affinity maturation of the antibodies produced.
For a vaccine to be immunogenic enough, DC activation, that can be achieved by adjuvants, is essential. Live attenuated and inactivated whole-cell vaccines are considered “self-adjuvanted” as they naturally present sufficient PAMPs to activate innate immune cells, including DCs; thus, promoting a robust antigen-specific immune response. In contrast, subunit vaccines generally require different types of adjuvants to enhance and/or drive the immune response in the desired direction [15, 17].
Viral outbreaks appear when there is a sufficient number of susceptible individuals within a nearby population. Although susceptibility is a balance between host factors (high/low resistance) and pathogens (high/low virulence), in many cases it reflects a lack of prior contact with a given pathogen. In general, this is related to the emergence of new viruses or the lack of effective vaccines against known viruses. As pointed above, the development of effective vaccines is not an easy task against certain viruses. We are still lacking vaccines for some of the most lethal viral infections, including HIV and MERS-CoV, among others. These pathogens are difficult to tackle, as we do not fully understand their mechanisms to evade the immune system or how to elicit protective immunity against them [13]. However, encouraging progress is being made against these pathogens and there are currently several “pipeline vaccines” in development, such as RSV, universal influenza vaccine, and SARS-CoV-2 [18, 19, 20]. Apart of SARS-CoV-2 for obvious reasons in the current pandemic, there is an urgency to have a universal influenza vaccine that provides a broad and durable protection from influenza virus infection. Yet, the high level of antigenic diversity and variability, and antigenic drift in the surface antigens, enable these viruses to escape antibody-mediating neutralization [21]. On the other hand, there is a number of vaccines currently licensed, including the influenza A virus vaccine, that provide incomplete protection, especially in high-risk groups [22]. Mumps outbreaks observed in Ireland, United Kingdom and United States in vaccinated subjects with Measles Mumps Rubella (MMR) vaccine is another example [23]. Different factors have been postulated to contribute to mumps outbreak, including waning immunity and primary and secondary vaccine failure. Yet, their actual contribution is not fully understood [23].
Vaccine efficacy must consider different target populations as well. Adaptive immune response to vaccines may be limited in newborn and the elderly. Early in life, immune responses are dampened compared to adults [24, 25]. Neonates have underdeveloped germinal centers in lymph nodes and the spleen, and low expression of B cell receptors which in turn results in low levels of primary IgG responses to infections and vaccines [26]. As we age, our immune system undergoes age-related changes that lead to progressive deterioration of the innate and the adaptive immune responses, this is termed immunosenescence. The most common features of immunosenescence are short-lived memory responses, impaired response to new antigens, increased predisposition to autoimmune diseases and low-grade systemic inflammation (inflammaging) [27, 28]. Immunosenesence results in increased susceptibility to infections and deficient response to vaccination causing high hospitalization and mortality rates. For example, influenza vaccine efficiency has been reported to be 17–53% in the elderly, compared with the 70–90% efficacy in young adults [29]; and vaccination with Varicella zoster virus (VZV), also an important pathogen in elderly people, only partially prevents reactivation of herpes zoster [27].
If the difficulties listed above are outlined for existing or developing vaccines, quickly obtaining an effective vaccine to urgently control a new virus outbreak is almost an impossible task in the short-term as pointed above. This is well exemplified by the SARS-CoV-2 vaccine race pushed by the devastating COVID-19, with more than 100 vaccine candidates in the running. It is considered that no less than 1 year will last the time until the first licensed vaccine can provide protection in the best scenario [30]. This, in spite of greatly shortening the usual clinical development time and regulatory obstacles for a new vaccine and, therefore, without knowing its true performance and/or safety in the medium term compared to other authorized vaccines [31].
It has become evident from epidemiological, clinical and experimental data that some conventional whole-cell vaccines, like BCG and others, also provide resistance to infectious diseases not related with the specific pathogen targeted by the vaccine [32, 33, 34]. Much of these non-specific “heterologous” effects appear to depend on the activation of innate immune cells by the PAMPs contained naturally in these vaccines [10], although other mechanisms such as cross-reactive epitopes between different pathogens could also account for this protection in some cases [35].
Immunological memory, understood as the ability to “remember” past encounters with pathogens, has been classically attributed to the adaptive branch of the immune system exclusively, by virtue of the antigen-driven clonal expansion of T and B lymphocytes and exemplified by the mechanism of conventional specific vaccines pointed above. However, the notion that innate immunity was unable to induce immunological memory has been challenged in recent years, particularly from studies in organisms that lack adaptive immunity, such as plants or invertebrates, as well as early studies in mice lacking the adaptive immune system [8, 36]. Altogether, the term ‘trained immunity’ was coined to define an innate immune memory that lead the innate immune system to an enhanced response to secondary challenges [37]. Importantly, trained immunity seems to be underlying the heterologous effects of an increasing number of vaccines [38, 39, 40].
What is trained immunity? - Trained immunity is defined as the memory of the innate immune system, where an encounter with a first stimulus (e.g. a microbial insult) results in a subsequent long-term adaptation and enhanced non-specific response by innate immune cells against a secondary challenge (the same or unrelated), thus providing non-specific, broad-spectrum, long-term protection in case of infection [8, 9, 37, 41].
Which cells can be trained? - Trained immunity properties have been defined for distinct cell subsets of the innate immune system [9, 42], including natural killer (NK) cells and innate lymphoid cells [43]. Of note, training of myeloid cells [42], particularly monocytes and macrophages [44, 45], and more recently DCs [46, 47] and hematopoietic stem cells [48], have been extensively studied. Finally, the acquisition of this immunological memory has also been demonstrated to a lesser extent for non-immune cells [49].
How to get trained? - A wide variety of stimuli can train innate immune cells, particularly when considering monocytes and macrophages [9, 50]. Among infectious agents, live microorganisms such as the tuberculosis vaccine BCG [51], Candida spp [52] or viruses [53, 54]; bacterial components, such as flagellin, lipopolysaccharide, muramyl dipeptide [55], fungal components as β-glucan [52] or even helminth products [56]. In general, microbial ligands engaging some PRR, like C-type lectin receptors (CLRs), nucleotide-binding oligomerization domain-like receptors (NLRs) are well established training inducers, whereas those engaging toll-like receptors (TLRs) may have opposite effects depending on the TLR type and concentration [55, 57]. Intriguingly, not only infectious agents but also endogenous inducers and metabolites such as oxidized low-density lipoprotein or mevalonate can induce trained immunity [50].
What hallmarks define trained immunity? - In contrast to adaptive immune responses, epigenetic reprogramming of transcriptional pathways — rather than gene recombination — mediates trained immunity. This training phenomenon comprises three key hallmarks that occur at the intracellular level: increased cytokine production upon rechallenge, changes in the metabolism and epigenetic reprogramming [9, 58, 59], which eventually support increased protection upon infection.
Among those cytokines whose production is augmented after re-exposure in trained cells, proinflammatory molecules such as tumor necrosis factor α (TNF-α), interleukin (IL)-6, IL-1β and interferon γ (IFN-γ) are fairly constant [45, 52, 55, 60, 61]. Modulation of IL-10 varies between studies [45, 52, 56, 62, 63]. A noted shift from oxidative phosphorylation to aerobic glycolysis (Warburg effect) is the main change in cellular metabolism during the induction trained immunity [64]. Moreover, glutaminolysis, cholesterol synthesis and the tricarboxylic acid cycle are non-redundant pathways required for trained immunity to take place [64, 65]. Epigenetic reprogramming, mainly mediated by histone modifications, is one of the bases for the long-lasting effect of trained immunity [8, 66, 67, 68]. Immune pathway activation and changes in metabolism serve as basis for epigenetic rewiring [65]. As a result, epigenetic modifications have been found at the level of important promoters for the training process, which makes chromatin more accessible and conditions gene expression patterns of trained cells upon stimulation with a secondary challenge [69].
As a result of the whole process, enhanced, broad-spectrum, non-specific protection mediated by innate immune cells is found upon infection. This cross-protection has been observed for a wide range of human pathogens including fungi [51, 52], parasites [70, 71] and different bacterial infections [72, 73, 74, 75]. Importantly, induction of trained immunity has been proved to be effective against viral infections including yellow fever [76], influenza A virus [77] and others [78, 79]. In this line, the induction of this phenomenon has been also proposed as a tool for reducing susceptibility to emergent SARS-CoV-2 infection, as will be described at the end of the chapter [78, 80].
How long does trained immunity last? – Trained immunity phenotypes have been observed for months and up to one year after the training insult. This was initially controversial, as trained immunity properties had been attributed to short-lived myeloid cells such as monocytes or DCs [38]. In this regard, several studies have shown that modulation of bone marrow progenitors is also an integral component of trained immunity, supporting the long-lasting effect of this phenomenon [9, 81]. In this way, trained immunity inducers [82, 83, 84, 85] would be able to reprogram and induce expansion of hematopoietic progenitors with a particular bias to the myeloid lineage. Thus, bone marrow-derived mature cells would be also trained [86], showing improved clearance of infection [83].
Complementary to progenitor reprogramming, peripheral trained immunity induction would take place in tissue-resident cells [9]. This is especially relevant at the mucosal level, where cells encounter most of the infectious training inducers. Alveolar macrophage (AM) memory was demonstrated following viral infection [87, 88]. Training of these long-living cells led to increase antimicrobial properties, independently of systemic immunity [87, 89]. This local training of AM was further reproduced following respiratory mucosal administration of tuberculosis vaccine, being crucial for Mycobacterium tuberculosis clearance [90]. On the other hand, training of NK cells lead to long-lived, self-renewing, stable expanded cells with memory-like properties, both in an antigen-dependent or independent manner [91, 92, 93]. Finally, it was also reported that self-renewing long-living skin epithelial stem cells exhibited local trained immunity, providing faster wound healing in primed mice than in naïve mice [94, 95].
Non-specific effects of vaccines have been extensively studied and reported over the last decades. Although trained innate cells could partially account for these effects, involvement of adaptive immunity has also been suggested [96]. An adaptive immune mechanism of non-specific effects could be heterologous immunity; vaccine antigens can give rise to T cell cross-reactivity against other antigens that may confer some protection against unrelated pathogens [96, 97].
However, innate immune cells constitute the bridge between the intrusion of microbial threats and the activation of adaptive immunity. As said before, following sensing of pathogens by PRRs, activated innate immune cells secrete different factors and act as antigen-presenting cells (APCs) to initiate activation of adaptive immunity [98]. Thus, it would not be unexpected that trained innate immune cells, within their acquired enhanced properties, would be able to induce stronger adaptive immune responses [39]. In this regard, BCG vaccine, a well-known trained immunity inducer, has shown to enhance the antibody titer and alter heterologous T cell responses against a wide range of vaccines and unrelated infections [99, 100, 101]. In different experimental models, BCG-mediated protection against viral and Plasmodium infections was abrogated in the absence of T cells. In these models, BCG vaccination has been mainly associated with modulation of CD4+ T helper (Th) 1 responses. Similar observations have been found in different clinical studies [99]. Of note, BCG vaccinated human volunteers displayed a long-lasting heterologous Th1 and Th17 response upon stimulation with unrelated pathogens and TLR-ligands [38]. To some extent, similar observations have been found in other vaccines such as diphtheria-tetanus-pertussis (DTP) or measles vaccine [99].
As said before, trained immunity properties have been recently described also for DCs. As being the most professional APCs, they emerge as crucial bridge for potentiating adaptive immune responses. In this sense, DCs with high immunostimulatory properties that enhance adaptive immune responses via IL-1β release had been described [102]. More recently, programmed memory DCs have shown to increase Th1/Th17 immunity and confer protection during cryptococcosis [46]. Finally, different polybacterial preparations of whole-cell inactivated bacteria, have shown to prime DCs and induce enhanced Th1, Th17 and IL-10 T cell responses against related and unrelated stimuli [103, 104]. This capability of modulating heterologous T cell responses by APCs have been also described to suppress pathogenic T cell immunity in experimental models of autoimmune encephalomyelitis [56].
As noted above, a hallmark of trained innate immune cells is the enhancement of some effector functions leading to increased non-specific resistance against a variety of pathogens. In this regard, β-glucan-trained monocytes show enhanced candidacidal activity and efficiently inhibit the C. albicans outgrowth [52]. Production of reactive oxygen species (ROS) has shown to be also affected by the induction of training. Thus, BCG-trained monocytes [45], β-glucan-trained macrophages [105] or β-glucan-trained neutrophils [106] produced increased amount of ROS following different challenges. Finally, increased phagocytosis and production of microbicidal molecules have been observed in β-glucan-trained macrophages [70, 105]. Mechanisms underlying this enhanced effector function could be an intrinsic cell reprogramming as consequence of the training, as well as be supported increased expression of different PRRs and surface molecules [45, 60, 87]. Altogether, these enhanced effector responses could improve pathogen clearance by increasing host resistance.
On the other hand, a substantial part of the adaptive immune response is directed at recruiting other effector cells from the innate immune system to eventually resolve an infection. Both T helper and B responding cells release cytokines, antibodies, and other mediators that activate monocytes, macrophages, NK cells or neutrophils to clear extracellular and intracellular pathogens [107]. Multiple studies have demonstrated the importance of IFN-γ-mediated priming in the activation of macrophages [108, 109], produced by CD4+ Th1 and CD8+ T cells [107]. In this sense, it has been previously demonstrated that adaptive T cells render innate macrophage memory via IFN-γ-dependent priming [87, 89]. Furthermore, a deep crosstalk between Th17 and neutrophils have been widely demonstrated, via production of IL-17 and other related cytokines [110].
Taken into account the potential role of trained innate cells in both the induction of adaptive and effector responses, a notable amplification loop in the global immune response could be considered (Figure 1).
Effect of trained immunity on ongoing immune responses. Induction of trained immunity allows trained cells to enhance adaptive immune responses and vice versa, final effector functions of trained cells can be further potentiated by enhanced adaptive responses.
Based on trained immunity pillars, a next generation of anti-infectious vaccines has been postulated, coined as ‘Trained Immunity-based Vaccines’ (TIbVs). TIbVs would be conceived to confer a broad protection far beyond the antigens they contain. By proper targeting of innate immune cells to promote trained immunity, a TIbV may confer non-specific resistance to unrelated pathogens while trained immunity memory is still present, in addition to the specific response given by intrinsic antigens [39].
A bona fide TIbV would consist of two main components: the trained immunity inducer(s) and the specific antigen(s). The antigen(s) mission is to generate an adaptive (specific) immune response as any conventional vaccine. The trained immunity inducers aim to promote the training of innate immune cells. This innate immune training would confer non-specific resistance against unrelated pathogens for a window of time (months) plus an enhanced adaptive immune response to the antigens present in the vaccine itself or from other sources (e.g., coming from eventual infections or bystander pathogens) [39].
Two additional concepts arise under the TIbV umbrella: i) trained immunity-based immunostimulants (TIbIs) and ii) trained-immunity-based adjuvants (TIbAs). The former (TIbIs) would induce the training of innate immune cells, so they would be ready-to-act against upcoming infections conferring broad non-specific protection while trained immunity is present, still enhancing adaptive immune responses following any eventual natural infection. The latter (TIbAs) would enhance adaptive responses against specific antigens incorporated either to the trained inducers as in bona fide TIbVs, or in a separated but combined vaccine [39] (Figure 2).
Different possibilities of trained immunity-based vaccines (TIbVs). Under the umbrella of trained immunity-based vaccines (TIbVs) different possibilities exist depending on their design and purpose. Bona fide TIbVs are those containing both trained immunity inducers and antigens in the same vaccine as occurs in conventional vaccines with trained immunity inducing properties. These vaccines show heterologous protection in addition to the specific response to the target antigen. TIbIs are intended just to confer non-specific protection by means of trained immunity induction beyond the intrinsic antigens they may contain. TIbAs are intended to enhance the specific response of other vaccines that are administered later, once trained immunity has been induced, or specific antigens combined in the same vaccine as any other adjuvant.
Following the above features, the TIbV concept can be applied to existing anti-infectious vaccines composed of microorganisms that show heterologous protection ascribed to trained immunity.
During the last decades, robust epidemiological data has demonstrated the role of certain vaccines leading to protection against heterologous infection with a high impact on overall mortality in children [111, 112, 113]. This protection could not only be explained by protection achieved by the target disease. Studies on MMR vaccination in high-income settings have also evidenced a reduction in non-target infections, particularly in respiratory infections [114]. A limitation for most of these epidemiological studies is that they do not identify the agent (viral, bacterium or parasite) responsible for the infection. These heterologous effects of certain vaccines conferring non-specific protection for a quite long time are believed to be largely due to non-specific stimulation of the innate immune system. It is not yet clear whether this is a direct reflection of trained immunity induction (i.e., acting as TIbVs) in every case. The fact that most of these vaccines use live-attenuated microorganisms, i.e., self-replicating agents, may suggest that a continuous stimulation of innate immune cells is necessary to obtain protection and/or to achieve a proper trained immunity for this purpose.
The BCG-Denmark strain was tested in randomized-controlled trials (RCT) in infants who normally did not receive the BCG vaccine at birth. These studies carried out in Guinea-Bissau demonstrated that vaccination at birth was associated with lower neonatal mortality, especially due to neonatal sepsis, respiratory infections, and fever [111, 115]. In these lines, a meta-analysis commissioned by the WHO concluded that BCG administration during the first month of life reduces all-cause mortality by 30% [116]. In these studies authors did not discriminate the etiology of infection (bacterial vs. virus); therefore, a reduction in viral infections may explain, to some extent, this result. However, in two studied carried out in India in neonates with BCG-Russian strain no such effect was observed [117]; suggesting that different immunological effect of diverse BCG strains may account for these discrepancies. A study carried out in infants to assess the impact of BCG vaccination on the incidence of RSV infection suggested a possible protective role for BCG vaccination against acute lower respiratory tract infection [118]. Other clinical studies have provided evidence suggesting a protective role for BCG on secondary viral infections [79]. In this regard, the impact of BCG vaccination on viral infection in human healthy volunteers has been assessed using the live attenuated yellow fever vaccine (YFV) as a model of viral human infection [76]. BCG vaccination induced epigenetic reprogramming in human monocytes, and these modifications correlated with IL-1β upregulation and the reduction of viremia, all these features being the hallmarks of trained immunity [76].
Similar protective effect of BCG was observed in several studies in elderly people regarding respiratory tract infections. BCG vaccination in subjects of 60–75 years old once a month for three consecutive months resulted in reduction of acute upper respiratory tract infection, concomitant to significant increase in IFN-γ and IL-10 compared with those receiving placebo [119]. A recent randomized trial of BCG vaccination was carried out in elderly patients (age ≥ 65 years) returning home from hospital admission, these subjects are at high risk to develop infections. The BCG vaccination increased the time to first infection (primary outcome) and decreased the incidence of a new infection [120]. Besides, results demonstrated that BCG vaccination resulted in lower number of infections of all causes, especially respiratory tract infections of probable viral origin, although no discrimination was made between respiratory tract infections caused by bacteria or viruses.
BCG has also been shown to enhance the response to vaccines directed against viral infections [79]. A clinical study in healthy volunteers demonstrated that BCG administration prior to influenza vaccination increases antibody titers against the 2009 pandemic influenza A (H1N1) vaccine strain, concomitantly with an enhanced IFN-γ production to influenza antigens compared with the control group [121].
The cold-adapted, live attenuated influenza vaccine (CAIV) has been shown to provide non-specific cross-protection against RSV in an experimental model of infection [122].
In a randomized pilot study conducted in healthy volunteers receiving a trivalent influenza vaccine, cytokine responses against unrelated pathogens were observed [121]. During the 2003–2004 influenza A (H3N2) outbreak, an open-labeled, nonrandomized vaccine trial was carried out in children 5 to 18 years old. Subjects received either trivalent live attenuated or inactivated influenza vaccine. Live attenuated influenza vaccine but not trivalent inactivated vaccine was effective in children administered during influenza outbreak, despite the dominant circulating influenza virus was antigenically different from the vaccine strain [123].
Measles vaccine (MV) is among the live vaccines that have been shown to have beneficial effects reducing all-cause mortality [124]. Randomized clinical trials and observational studies from low-income countries have concluded that measles vaccination is associated with decreased overall mortality and morbidity [100]. However, a systematic review carried out by Higgins and colleagues has pointed out that most of these studies were considered at high risk of bias [116]. Nevertheless, MV seems to induce a transient suppressive effect on both the lymphoproliferative and innate response evaluated in peripheral blood mononuclear cells (PBMCs) from children, with slight increase in innate immune response, measured by non-specific cytokine production [100]. It has been reported that following measles vaccination, the ex vivo production of both innate (IL-6 and TNF-α) and adaptive (IFN-γ and IL-2) cytokines decreases for 2 weeks, but levels of IL-2, IL-6 and IFN-γ are increased at day 30 post vaccination compared with baseline [125]. Differences in males and females have been reported, where girls seem to receive stronger beneficial effects. In this regard, a study of MV-specific innate responses following MMR vaccination found higher TNFα, IL-6 and IFN-α secretion, cytokines associated to trained immunity, in adolescent girls than boys [126].
There are currently only three countries where polio remains endemic. Thus, polio-free, high income countries are introducing the use of the inactivated polio vaccine (IPV). However, there are still many countries that use the live-attenuated oral polio vaccine (OPV). Despite current WHO policy to replace OPV by IPV, there is epidemiological evidence that supports that replacing OPV by IPV might have an impact on overall mortality [96], since OPV has shown strong non-specific beneficial effects even in settings where the incidence of the targeted infection is low. In this regard, campaigns to eliminate polio in West Africa have been associated with lower child mortality rates [127].
As pointed above, most of the vaccines described so far showing non-specific heterologous effects contain live-attenuated microorganisms. Nevertheless, fully inactivated bacterial vaccines have also been described conferring protection against viral infections, and some of them for a fairly long period of time. Interestingly, these vaccines are mucosal preparations that are administered daily for long periods of time (weeks/months) rather than single, or seldom, doses used in live attenuated vaccines. Thus, it seems that the much longer administration of these inactivated mucosal vaccines resembles the effect achieved by live vaccines on heterologous protection associated to trained immunity (Figure 3).
Trained immunity window by self-replicating and inactivated TIbVs. Trained immunity-based vaccines (TIbVs) containing live-attenuated self-replicating microorganisms (e.g. BCG) may require fewer administrations to induce an adequate trained immunity window of sufficient intensity, quality and/or duration than vaccines with dead microorganisms. Fully-inactivated TIbVs can be enhanced to induce trained immunity with a multiple dose schedule (e.g. MV130).
These vaccines are used for the prevention of recurrent infections in susceptible subjects, mainly associated to the respiratory and urogenital tracts [128, 129, 130, 131, 132, 133, 134]. Since they target infections occurring in these tracts, their administration is generally through mucosal tissues to obtain a better mucosal response [135, 136].
MV130 is a sublingual vaccine used to prevent recurrent respiratory tract infections [128, 129] containing inactivated whole-cell bacteria that are common pathogens in the airways. Its ability immunomodulating DCs has been addressed experimentally in vitro and in vivo. MV130 triggers the release of cytokines ascribed to trained immunity in different setting, including TNF-α, IL-1β and IL-6 [103, 137, 138]. Sublingual immunization of mice with MV130 induces a systemic Th1/Th17 and IL-10 enhanced responses against unrelated antigens [103]. Similar enhancement was shown in patients treated with MV130 where an increased T cell response to flu antigens were described [128]. MV130 was successfully used in infants with recurrent wheezing, a condition triggered in most cases by viral infections. It is noteworthy that the protective effect was also shown 6 months after discontinuation of treatment, which points to a long-lasting effect that fits with the memory ascribed to trained immunity (Nieto et al., under review). In this regard, MV130 has been shown to induce trained immunity and to confer protection against experimental virus infections (Brandi et al., under review). Recent studies have assessed the clinical benefit of MV130 as a TIbV in the context of recurrent respiratory infections in vulnerable populations such as patients with different primary and secondary immunodeficiencies showing a reduced rate of respiratory infections [130, 139] (Ochoa-Grullón et al., in press).
Although not considered vaccines but immunostimulants, these bacterial preparations are, like MV130, used for the prevention of recurrent respiratory infections. OM-85, one of the best studied, is composed of chemically treated bacterial lysates for oral administration, acting through the gastro-intestinal mucosa. OM-85 has been shown to be effective in experimental viral infections [140] and in children with recurrent wheezing [141], a condition triggered by viruses as noted above. OM-85 stimulates the release of proinflammatory cytokines such as IL-1β, TNF-α and IL-6 by macrophages [142], typical of trained immunity induction, as well as Th1 cytokines including IFN-γ [143]. It is not known, however, the role of trained immunity in their mechanism of protection. A recent study conducted in infants, the observed protection against respiratory infections under OM-85 treatment stopped when treatment was discontinued [144], which may point against the memory ascribed to trained immunity.
The non-specific mechanism of TIbVs against widely differing pathogens associated to the induction of trained immunity can be exploited clinically. This makes TIbVs as a ready-to-act tool to tackle disease outbreaks from different angles where conventional specific vaccines have proven their limitations:
Newly emerging disease outbreaks, with no conventional vaccines available. Even in the presence of therapeutic options, vaccines are the best tool to prevent infections. However, even with worldwide efforts, getting a vaccine to the public takes time. In addition, side effects, dosing issues, and manufacturing problems can all cause delays [3]. Herein, using available TIbVs could mitigate the devastating consequences of emergent outbreaks by means of non-specific protection, until a suitable specific vaccine is available.
Newly emerging disease outbreaks, first coming vaccines with partial efficacy. Even if a vaccine gets available to the market, conventional strategies might raise some issues. The unpredictable identity of largely unknown emerging pathogens, the lack of appropriate experimental animal models, and the time for faster developing may give raise to an upcoming vaccine with no full efficacy [3]. On the other hand, limitations of current vaccines, such as mumps, also include a low efficacy resulting from an unacceptable drop in the immune response over time, requiring re-immunization [145]. In these contexts, the administration of a TIbV prior to the specific vaccine may enhance the response to the latter (111).
Re-emerging disease outbreaks, pathogens with high mutation rates and loss of vaccine efficacy. Mutations are the building blocks of evolution in any organism. Viruses are among the fastest evolving entities, especially RNA viruses such as influenza. Implications in conventional vaccine design are numerous, as a high mutation rate makes it hard to design a vaccine that is universally effective across many years. As a result, this makes a vaccine effective for shorter and raises the need for yearly vaccination programs [22, 146]. Since the underlying mechanism of TIbVs extend well beyond their nominal antigens and have a broad-spectrum of protection, TIbVs could overcome the troublesome of highly specific vaccines that promote antigen variant switching [147].
Disease outbreaks in vulnerable populations. During infectious disease outbreaks, vulnerable populations are usually disproportionately affected due to an interplay of immunological, epidemiological, and medical factors, which leads to sub-optimal or even under-vaccination [148]. This is well exemplified in the elderly population, where successful vaccination against important infectious pathogens which cause high morbidity and mortality represents a growing public health priority. Age-related immunosenescence and ‘inflammaging’ have been postulated as underlying mechanisms responsible for decreased response and high mortality, including during COVID-19 pandemic or influenza season [80, 149]. Therefore, more potent vaccines are needed. In this regard, the induction of trained immunity by the use of TIbVs is proposed to overcome the immune dysfunction found in these individuals [28]. Thus, elderly has been proposed as one of the groups to benefit from the use of TIbVs, including severe COVID-19 disease, with the aim of potentiating the immunogenicity of their vaccination [80]. Moreover, some types of immunodeficiencies or immunosuppression may benefit from TIbVs. These formulations, by means of tackling both branches of immunity, especially the innate compartment, may be an achievable alternative to reinforce protection or optimize immunogenicity of vaccination in this population [130, 139].
Altogether, harnessing the TIbV concept has been suggested as a crucial step in future vaccine development and implementation, because a wide range of clinical applications may benefit to some extent from their use [150].
Despite the tremendous financial and scientific effort invested to rapidly obtain a prophylactic vaccine against SARS-CoV-2, only the first one has been licensed in December 2020. Although this means less than a year since the declaration of the pandemic by the WHO, which is an unprecedented achievement, in the meantime, two pandemic waves of COVID-19 and more than 1.5 million deaths have been declared worldwide. Therefore, alternative strategies have been considered to fill the gap until a safe and effective vaccine is available. As noted earlier in this chapter, TIbVs can play an important role for this purpose by increasing host resistance to other pathogens, including viruses.
A bunch of recent studies have been published supporting the role of certain vaccines, including BCG, OPV and measles, as a possible successful strategy to reduce susceptibility and severity to SARS-CoV-2 through trained immunity induction [80, 151, 152]. Thus, clinical trials are currently being conducted to find out the contribution of trained immunity as a preventive tool in the context of COVID-19 pandemics [153]. In a prospective observational trial, 255 MMR vaccinated subjects were followed searching for COVID-19 cases, thirty-six presented COVID-19 but all with a remarkable mild course [154]. Recent studies have also suggested a potential benefit of influenza vaccine on the susceptibility and the outcome of certain infections including SARS-CoV-2. In this sense, a particular attention has been focused on a high-risk population, the elderly. In a study conducted in Italy, influenza vaccination in people aged 65 and over was associated with a reduced spread and a less severe clinical expression of COVID-19 [155].
Finally, in addition to the potential role of TIbV conferring resistance against SARS-CoV-2 infection, they can eventually be used to increase efficacy of specific anti-COVID-19 vaccines, when available, especially in vulnerable population. In this sense, implications of vaccination route and mucosal immunity have also been raised as a key aspect in the development of safe and effective prophylaxis interventions against SARS-CoV-2. Most formulations in development are parentally administered; only a few COVID-19 vaccine candidates are administered by mucosal routes. Still, studies indicate that even if mucosal immunization against coronavirus does not confer sterilizing immunity, the ability to induce anti-SARS-CoV-2 IgA responses in the airways may prevent virus spread to the lung and avoid respiratory distress [156]. In this regard, mucosal TIbVs could enhance the mucosal response of specific COVID-19 vaccines acting as TIbAs by combining them as pointed above in those especially vulnerable subjects.
Viral outbreaks can cause epidemics and pandemics if the route of transmission allows for the rapid virus spread. Given the ease of travel and the global exchange of potential transmitting agents, these situations will be increasingly frequent in the future. Preventing the spread of a virus outbreak caused by a highly contagious agent is not easy in the absence of effective therapies or preventive measures. Although the development of effective prophylactic vaccines specific for the threatening virus is the final goal when possible, this requires a minimum time of almost a year in the best possible scenario. Meanwhile, the consequences of the spread of a deadly virus can be devastating, as it is exemplified during the COVID-19 pandemic. This scenario may also take place in the case of re-emerging viruses tackled by partial efficacious vaccines. In such situations, harnessing the heterologous non-specific protection of some existing vaccines with a known safety track record is an interesting possibility. This protection may be critical for vulnerable subjects and/or for highly exposed individuals, like healthcare workers.
Non-specific protection of some vaccines is thought to be mainly dependent on their effect on the innate immune system. Increasing evidence gathered over the past few years points that innate immune cells show memory-like features when properly activated. This memory termed “trained immunity” has been associated with the non-specific protection of vaccines. The concept of “trained immunity-based vaccine” (TIbV) has been drawn to exploit the potential of trained immunity in designing novel vaccines or to redefine bacterial-derived preparations conferring broad protection against widely differing pathogens. As trained immunity may have implications on the adaptive immune response and vice-versa, its potential to provide enhanced immune responses is quite broad whether considering natural infections or following vaccination.
Taken advantage of the current COVID-19 pandemic, a number of clinical trials have been launched with putative TIbVs in order to address protection in highly exposed subjects. The results are eagerly expected as these initiatives may be considered as a proof-of-concept supporting their use in future epidemics/pandemics to fill the gap until a specific vaccine is available. Nevertheless, as trained immunity can be achieved by different inducers, it is unlikely to obtain the same degree of protection, duration, etc. for all of them, which may also depend on the biological behavior and the route of transmission of the threatening pathogen. As in most instances rapidly spreading viruses are airborne and primarily infect the mucosa of the airway tract, induction of trained immunity at the local mucosal level can confer a more adequate protection. This may be an opportunity for mucosal TIbVs as compared to those given parenterally.
Trained immunity may justify heterologous protection of vaccines, help to explain their underlying mechanisms, open avenues for next generation of vaccines, or be proposed to tackle outbreaks by new pathogens as described here. However, this is an emerging field that requires more clinical data before being a reality in the clinical practice; not only to be used against infectious outbreaks, but to fight against recurrent infections in vulnerable subjects for whom no effective vaccines are yet available.
JLS is the founder and CEO of Inmunotek SL, Spain, a pharmaceutical company that manufactures bacterial vaccines. LC and PS-L are employees of Inmunotek.
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