Mechanical parameters of materials extracted from the tests.
The application of acoustic emission (AE) technique in monitoring the safe condition is a useful technique in steel and concrete structures, whereas its application is restrained in masonry structures due to the layered property. Qualitative and quantitative analyses were investigated in this research to improve the AE application in masonry structures. For quantitative analysis, an improved localization method is proposed to give more reliable crack localization results. In the proposed method, the parameter ξ on the behavior of inhomogeneity of the monitored structure could minimize the unavoidable propagation delay caused by the layers in the masonry structure. The rest results approved the reliability of the proposed method in masonry structures. For qualitative analysis, the parameter analysis, including the cumulative AE event, frequency distribution, time-scaling exponent, and b-value, was adopted to monitor one historical church and was approved to be useful.
- acoustic emission
- masonry structures
- quantitative analysis
- qualitative analysis
- crack localization
Acoustic emission (AE) is the class of phenomena whereby transient elastic waves are generated by the rapid release of energy from a localized source or sources within a material. Clearly, an AE is a stress wave that travels through a material as the result of some sudden release of strain energy. By investigating their origin and characteristics, AE techniques provide an insight into the deterioration processes of a tested object, especially for the monitoring and nondestructive testing of the structural integrity and general quality.
Significant research work has been published in relation to the use of AE sensors for monitoring the health of structures in civil engineering, especially for concrete structures. The most important applications of AE to concrete elements started in the late 1970s, when the original technology developed for metals was modified to suit heterogeneous materials [1,2]. Some fundamental studies with small-scale specimens have shown that, in principle, AE analysis is an effective method for damage assessment . Research from various laboratory loading tests to full-scale models of real structural components was intended to relate observed AE characteristics to failure mechanisms in reinforced or prestressed concrete [4–7]. Some applications were tried to evaluate the structural integrity, load-carrying capacity, or eventual failure for real civil engineering structures such as concrete bridges and so on . Also, a continuous monitoring of a whole structure is applicable (e.g. to detect wire breaks of prestressing tendons) . The development of the corresponding AE equipment, such as wireless monitoring system with microelectromechanical system (MEMS) sensors , also furthers the AE research.
As AE gained importance for concrete structures, its application for masonry structures is gradually employed . Huge numbers of ancient masonry structures, such as towers and bridges, are present all over of the world. To preserve this inestimable cultural heritage, a sound safety assessment should taken into account the evolution of damage phenomena . In this respect, the AE monitoring technique can be highly effective. Some researchers  have successfully applied AE techniques to monitor masonry buildings, towers, and bridges. In these researches, the interpretation of AE rate has been put forward to monitor the criticality of the ongoing process, and the “
However, unlike the conditions in concrete, AE applications in masonry are still at an early stage. The reason is that AE is applicable for homogeneous or quasi-homogeneous materials (e.g. metallic and concrete) with good acoustic transmission. However, its application on heterogeneous materials, such as masonry, is much more problematic, especially in the crack source localization problem. Attempts were made by Carpinteri et al.  by involving the location of cracks during an on-site monitoring campaign. Although a large amount of AE events were detected, only a small percentage of them could be located. Damage location in masonry arch bridges was performed by Tomor and Melbourne  by simply applying a large set of AE sensors and identifying the sensors at which most damage was detected.
This paper focuses on the applicability of AE technique in the monitoring of masonry structures based on quantitative and qualitative analyses. To address these issues regarding the heterogeneous problem, a series of pencil-lead break tests were carried out on a masonry bridge and a historical church was monitored by the AE technique. The results are discussed in this chapter.
2. Quantitative analysis
Quantitative analysis is also called the signal-based AE technique, and the time series of AE events are recorded along with their waveforms. Quantitative methods allow a more accurate characterization of the fracture process and try to describe the nature of a source using special methods, such as localization and moment tensor analysis. The goal of quantitative AE analysis is to enumerate and explain the source of an AE event. The principle is that AE burst signals within a given time window are detected by more than one sensor and grouped to an AE event that can be associated with an AE source. Source localization method is one of the important ones adopted in this method.
The crack localization of AE sources is important to evaluate the areas of active damage in the monitored structures. The localization issue is normally solved by triangulation methods based on acoustic signal trajectories . Usually, these methods rely on the elasticity modulus, the propagation mode, and signal attenuation caused by the heterogeneity and anisotropy of the material. In this part, the classical localization method was summarized briefly.
2.1. Classical localization method
In a theoretical model, with wave propagation velocity
For each sensor
where subscript 1 is related to an arbitrarily chosen reference sensor (e.g. the closest one to the crack source).
If more than four arrival times are available for one event, the equation will be overdetermined. The least-squares method are adopted to minimize the residuals, where the error for (
Considering Equation (5) is linear, and the issue can be solved iteratively until convergence .
2.2. Velocity field of AE-
v P i ( r )
As shown in Equation (1), the acoustic wave velocity field
The refraction and reflection of the wave at the layers is unavoidable for masonry materials. Because the reflection phenomenon mainly leads to the decrease of the signal amplitude and of incident energy density, we only take propagation effects related to the refraction of AE wave into consideration. From Figure 2, the propagation delays (denoted as
Normally, the difference of velocity in the two different paths for one sensor event is not so obvious and
2.3. Test set-up and velocity field modification
Several pencil-lead break tests based on a two-arch masonry bridge model are conducted in this research to improve the source localization problem in the masonry structure.
2.3.1. Monitoring system of AE
The AE monitoring set-up consisted of six piezoelectric (PZT) sensors and six control units and a PC-based multichannel monitoring system called SAMOS AEwin (Sensor-based Acoustic Multichannel Operating System) that is manufactured by Physical Acoustic Corporation (PAC). Appropriate AE sensor types are important in the fracture monitoring of concrete structures. Because concrete is known to be a highly attenuating material, lower-frequency sensors are suitable for AE studies. The maximum aggregate size in concrete for the present study is 20 mm, and 3500 m/s is normally used as sound velocity in concrete. Using the relation
2.3.2. Bridge model and material property
A two-arch masonry bridge model was designed and the scale of the bridge model is 1:2 and it is 5.90 m long, 1.60 m wide, and 1.75 m high according to the theory of models. Bricks with a uniform size of 130×65×30 mm were made by hand. The mechanical properties of masonry brick and mortar were selected to better represent the real historical bridges. The bridge has two masonry abutments and a central pier. The abutments set on basements are built by concrete and anchored to the ground with special reinforcements, as shown in Figure 4. The details of the bridge can be found in our previous paper.
Before the tests, it is necessary to evaluate the mechanical properties of the bridge, such as the basic material (i.e. the masonry).
As shown in Figure 5, different kinds of laboratory tests have been conducted to estimate the mechanical parameters of the bridge. Besides, tests about the mortar itself and on the concrete to support the abutments were also performed. The key mechanical parameters extracted are the Young’s modulus
2.3.3. Tests of velocity field
As shown in Figure 6, sensors (
The test results of the detected velocities are shown in Figures 7 and 8. The labeled velocity
In Figures 7 and 8, the velocities, both on surface and inside the masonry, show that the velocity decreases clearly with the increasing propagating distance. The explanation is that the transient wave changes its mode from longitudinal to shear and/or to surface waves and vice versa due to the refraction and/or reflection during propagation in different phases. The longer the propagating distance is, the more mode change happens, which causes a bigger deviation of the actual wave propagation path Γ
From Figures 7 and 8, we can see that there is a great difference between the
2.3.4. Modified source localization method in masonry
Based on the classical method, a modified method is proposed in this part. The basic idea of the source localization in masonry material is similar as that in concrete. However, modifications for propagation delay are implemented. We still take the geometry distance
2.3.5. Validation of the modified localization methods
Pencil-lead break tests are conducted to produce AE source on the right-side surface of the masonry bridge. As shown in Figure 10, six sensors described in Section 2.3.1 are attached to the surfaces. Nineteen different points were selected to make a pencil-lead break (artificial source), and a pencil was broken eight times for each point, so totally 152 signal results are recorded. Nine hundred twelve AE events were obtained from the six sensors in this test and then all the 19 points were source localized following the procedure shown in Figure 9.
The localization results are shown in Figure 10 for both the proposed modified and traditional methods. It is clearly shown that the location accuracy changes with the source break position. According to the accuracy, we divided the break points into three groups. As the dashed line shown in Figure 10, points 3 to 8 inside the central area of the sensor network have the best accuracy for localization for both methods. In the second group, points 2, 9, 10, 11, and 12, distributed on the nearby region of the sensor network, comprise the second group. Points in the third group are the rest of the points, far from the sensor network.
In the first group, the two methods both get the ideal result, the errors are all smaller than 6 mm, and most crack sources can be detected. In the second group, the proposed modified model gives better localized results than the traditional method. The errors value (
From the test results, compared to the traditional method, the proposed modified method can give better source localization results for the masonry structure in all the three group conditions.
3. Qualitative analysis
Qualitative analysis, also called the parameter-based AE technique, extracts only parameters but the signal itself. The parameters usually used are arrival time, amplitude, duration, number of oscillations, and so on. The typical methods employed in the parameter-based technique are ring-down counting and event counting, in which the event intensity is measured by the oscillation number NT, and the oscillation number NT increases with the signal amplitude.
To express the application of qualitative analysis, we applied the AE technique to monitoring one historical chapel, which is located in north Italy of Sacro Monte di Varallo. In this monitoring, our task is to investigate the stability of the painted plaster walls and injuries with the technical AE. The monitoring structure is the Chapel XVII of the Sacred Mountain of Varallo. The cumulative AE event, frequency distribution, time-scaling exponent, and
3.1. Scenario of the monitored heritage chapel
The Sacred Mountain of Varallo is one of the oldest Italian constructions in its style. It was constructed in 1491 by San Francesco. The Sacro Monte was built on a rocky foundation, located on the slopes of Mount of Three Crosses, and River Sesia is on the left side. This natural formed terrace (600 m) soars up the historic center of Varallo (450 m) about 150 m.
The Sacred Mountain of Varallo consists of a basilica and 45 chapels, either isolated or inserted into the large monumental complexes, famous by more than 800 life-size painted statues, in wood and terracotta, which dramatically illustrate the life, passion, death, and resurrection of Christ. These interiors are vividly decorated with fresco paintings. Figure 11 is a point view of Sacro Monte.
The first monitored structure by AE technique was chosen as the Chapel XVII, which tells the story of the transfiguration of Christ on Mount Tabor, as shown in Figure 12. Chapel XVII was constructed starting from the foundations in 1572 but was finished only in the 1760s.
As shown in Figure 13a, the frescoes inside the Chapel XVII are the outcome of the brothers Montaldo, who also are the makers of the decoration of the dome of the Basilica of the Sacred Mountain. The statues attributed to Peter and John Francis Petera Varallo Camasco by Soldo were finished in the 1770s, as shown in Figure 13b.
3.2. In-site monitoring by AE technique
The target is to set the sensors for the monitoring of AE signals from a lesion in the north wall of the chapel and a detachment of the fresco. On the other hand, some of the terracotta statues in the chapel were also analyzed (Figure 14).
Some necessary previous operations were carried out by professional restorers for attaching the AE sensors on the wall. First, areas were selected and prepared for monitoring with the films of Japanese paper, of which the surface was then stretched out a hand of light “Paraloid”, as shown in Figure 15a. This is one kind of acrylic resin that is used in restoration as a consolidation at low concentrations (2–4%) or glue at higher concentrations. As shown in Figure 15b, the “Paraloid” here provides a good basis for the bonding of the AE sensors.
The sensors have been arranged in positions useful to monitor simultaneously both the progress of the lesion and the detachment of the plaster. The detailed locations of the sensors are shown in Figure 16.
The AE signals were picked up by a transducer and preamplified and transformed into electric voltage. Unwanted noisy signals were then eliminated by filtering frequencies, such as the vibration caused by the mechanical instrumentation, which is normally lower than 40 kHz. The signals were therefore analyzed by a measuring system that counts the signals that exceed a certain set voltage threshold measured in volts.
PZT sensors are set on a frequency range between 50 and 400 kHz. The data acquisition system consisted of six data storage provided trigger, six preamplified sensors, a central unit for the synchronization phase, and a threshold detector. From this monitoring system, microcrack localization is performed and the safe condition of the monitored specimen can be determined.
3.3. Results of the process based on the monitoring data
The monitoring work begun on 15:00 of April 28, 2011, and was planned to last for 6 months. In this part, only the monitoring data until 12:00 of June 4, 2011, were studied.
Based on the monitoring data, the qualitative analysis of the data is mainly based on five techniques: the cumulative events analysis, the time dependence analysis, the
According to the above qualitative analysis of the monitoring results, we know that the lesion region of the Chapel XVII appears to be stable during the monitoring period with some microcrack occurrence. As shown in Figure 19, the region around sensor 2 should be a more active region for lesion, and we should pay more attention on this region. On the contrary, the condition is not so good for the detachment area and the detachment phenomenon occurs with high frequency, especially for the region around sensor 6, as shown in Figure 19. Some maintenance measures should be implemented on this region.
4. Discussion and conclusions
Due to the increasing demand of structural retrofit and strengthening, monitoring techniques have received high attention. AE is one of the nondestructive monitoring techniques, which is widely employed for the cracking analysis in steel and concrete structures. However, the application of AE techniques to monitor masonry structures is complicated due to the fact that attenuation and wave propagation are highly dependent on the heterogeneity of the material.
Based on this problem, quantitative and qualitative analyses were proposed in this research to make the AE monitoring in masonry possible and reliable.
Crack localization is an important function in the quantitative analysis to offer the information of the active damage region. Considering the complicated material properties of masonry making the traditional localization method cannot be used directly, one modified method was proposed in this research. The proposed modified method of localization permits giving reasonable location results. In the proposed modified method, a modified factor
Besides the quantitative analysis, the qualitative analysis can also be used to monitor masonry structures. The application of the qualitative analysis was explained by monitoring one historical chapel. The cumulative events analysis, the time dependence analysis, the
In conclusion, quantitative and qualitative analyses proposed in this research can help to make good use of the AE technique to monitor masonry structures, and sometimes, better results can be driven if the two analysis methods can be used simultaneously.
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