From Noise Levels to Sound Quality: The Successful Approach to Improve the Acoustic Comfort

This work aims at presenting the experience of the authors in applying the “product sound quality” approach to the noise signals recorded at the operator station of some earth moving machines (EMMs) in order to improve the acoustic comfort for the operator. For industrial products, the concept of “product sound quality” was defined by Blauert and Jekosch as “...a descriptor of the adequacy of the sound attached to a product. It results from judgements upon the totality of auditory characteristics of the sound, the judgements being performed with reference to the set of those desired features of the product which are apparent to the users in their actual cognitive, actional and emotional situation” (Blauert & Jekosch, 1997). Referring to the operator station of an EMM, health and quality of the workplace are both important aspects to be taken into account. Therefore the reduction of the noise exposure levels and the improvement of the noise quality in terms of low annoyance are both key elements. Unfortunately, these aspects are not automatically correlated. According to the mandatory provisions, the exposure to noise must be assessed by means of physical parameters that have proved to be inaccurate indicators of subjective human response, especially for sounds exceeding 60 dB (Hellman & Zwicker, 1987). This chapter collects the main results of the research carried out by the authors in the last five years in order to overcome this problem and to identify a methodology that is able to establish the basic criteria for noise control solutions which guarantee the improvement of the operator comfort conditions (Brambilla et al., 2001). All the results presented below refer to investigations carried out on compact loaders. The particular interest in this kind of machine is due to the fact that it is widely used not only for outdoor work but also in the activities of building construction and renovation. In addition, the compact loader is one of the worst machines as far as the noise emission is concerned. Due to its compactness, indeed, the operator station is located just over the engine compartment which cannot be completely insulated from the outside due to overheating problems. As a consequence, noise and vibration levels at the operator station are extremely high, causing very uncomfortable conditions for workers. Although the enforcement of the results described in this work is limited to the assessment of annoyance for this kind of product, the philosophy of this approach has a general validity which is to be customised for each different application.


Subjective listening tests
Listening test results show a higher variance than that usually encountered in results obtained using instrumental measurements (Blauert, 1994).However, this high uncertainty can be greatly limited by choosing the most appropriate psychometric technique depending on the signals to be characterised and on the listening jury (Fiebig & Genuit, 2010).

Psychometric techniques
The several psychometric techniques can be broadly divided into two groups: the absolute procedures and the relative procedures (Van der Auweraer & Wyckaert, 1993).In listening tests following the absolute procedures, the subject has to listen to a sound and judge it referring to one or more of its attributes.In listening tests following the relative procedures, on the contrary, the assessment by the subject results from the comparison between at least two different sounds.In general, the absolute classification of a set of sound stimuli or their arrangement in an ordered list according to some criterion, is a process which sometimes can be inappropriate as it involves a series of psychological factors which are uncontrollable.In addition, when the sound stimuli chosen for listening tests are very similar with respect to certain attributes, tests according to absolute procedures can be very difficult, especially if they involve nonexpert subjects.In these cases it is advisable to use a relative procedure (Bodden et al., 1998).A further classification of psychometric procedures is based on the distinction between non adaptive and adaptive procedures (Gelfand, 1990).The non adaptive procedures include "classic" methods such as: -the sequential procedures (method of limits, method of adjustment), for which the listening level of the sound stimulus is varied step by step or continuously, but always with an ascending or descending sequence (from the lowest to the highest level or vice versa); -the non sequential procedures (method of constant stimuli), for which the listening level of the sound stimulus changes according to a predefined random sequence.
The adaptive procedures include methods such as the Békésy's Tracking Method, the Up-Down (Staircase) Method and the PEST procedures (Gelfand, 1990).In these procedures it is necessary to adjust the listening level of a sound stimulus on the basis of the answer given by the subject referring to the sound stimulus previously heard.

Rating scales
In listening tests the choice of the rating scale on which the subjects express their opinion is a key element to avoid ambiguity in the responses.According to a classification proposed by Stevens in 1951, the rating scales can be divided into: nominal scale, ordinal scale and interval scale (Stevens, 1951).
In nominal scales, variables take values represented by names or categories.These values cannot be put in order or treated algebraically.The only relationship that can be established between the various results is that of equality or diversity.
In ordinal scales, variables take values which can be sorted by some criterion.Relationships of "greater", "equal", "less" can be established between the different results but without any possibility to establish the distance between classes.
In interval scales, each variable is represented by a quantitative value.Therefore, either the different positions on the scale or the distances between the values are significant.In particular, the amplitudes of the intervals between equidistant positions on the scale represent equal differences in the measured phenomenon.
Depending on the type of scale chosen for tests, the most appropriate methods for statistical analysis have to be identified.For nominal and ordinal scales non-parametric statistical methods are preferred (Spearman correlation coefficient, Kendall's correlation coefficient), while for the interval scale the parametric statistical methods are more suitable.

Procedures applied to the subjective investigations referring to loaders
The binaural noise signals recorded at the operator station of the compact loaders under test were all very similar with respect to the perception of annoyance.A direct estimation of them with respect to this attribute following an absolute psychometric procedure would have been very hard, especially for non expert subjects.On the contrary, a relative comparison between sounds made the task much easier for the subject and made the detection of the difference among the sound stimuli easier to be assessed.So, the listening tests performed in the several investigations were all carried out according to the relative procedure of paired comparison (Kendall & Babington Smith, 1940).

The listening sequence of sound stimuli
According to the paired comparison procedure, each sound stimulus is directly compared to the others and the subject is asked to give his opinion after listening to each pair.In the several experiments, the classic and the modified v e r s i o n s o f t h i s p r o c e d u r e w e r e b o t h applied: in the classic version, the subject had to choose the sound he preferred in each pair and no ties were permitted; in the modified version, on the contrary, the subject was permitted to judge the sounds in the pair equally (David, 1988).
In any case, the main advantage of this procedure was that the subject was asked to judge only two stimuli at a time and this helped his concentration and reduced the probability for him of inconsistent judgments.
The number of possible pairs from a group of n sound stimuli is given by the number of combinations of two elements taken in this group, namely by : In the listening tests, the two sounds of each pair had always the same duration so that the judgement given by the subjects was not influenced by a different listening period.In addition, the two sound stimuli were always separated by a pause so that the subject could distinguish each of them and was not confused by their similarity.The duration of this pause, however, was not so long as to impair the memory of the first sound heard by the subject.
In order to avoid any sequence effect, all the pairs were arranged in a random sequence according to the well established digram-balanced Latin Square design (Wagenaar, 1969).In such a way the first pair to be judged and the order of the pairs in the sequence were different for each subject.

The listening session
All the listening tests were performed in the laboratory, under stable, controlled boundary conditions, with the great advantage of high reproducibility of the test results.
The sound stimuli were presented to the subjects through a high-quality electrostatic headphones (STAX Signature SR-404), with a flat response in the 40-40000 Hz frequency range, after being modified to take into account the transfer function of the headphones and the specific sound card.Listening through headphones reduces the ability of a correct spatial sound localization but for sounds recorded in earth moving machines this effect is not so important as the frequency content is concentrated in the medium-low frequency range that is not directional.Each listening session started with a learning phase during which the person responsible for the experiment gave the subject verbal instructions needed to understand the procedure for the test.This phase was a critical point of the listening session.An interaction between subject and the experimenter was necessary in order to clarify possible doubts before performing the test.This interaction, however, should not be excessive in order not to influence or interfere with the judgements given by the subject.At the end of this phase, the test started.The subject, after listening to each pair of sound stimuli, was allowed to listen to the pair again as much as necessary.When ready, he gave his rating according to the rules of each specific investigation.Each listening session ended when the subject had judged all the pairs of sound stimuli in the sequence.The same procedure was then repeated for all the subjects of the jury involved in that specific test.

The jury of subjects
In listening tests each subject of the jury acts as a measurement device to measure his own perception; so, he must have normal hearing.A further important aspect to take into consideration in the choice of a listening jury is the experience of the subjects involved in the tests.This is related to their familiarity with listening tests and/or with the sounds under examination (Brambilla et al., 1992).
In the several investigations aimed at improving the acoustic comfort at the operator station of compact loaders, the operators were only seldom involved in the listening tests because of the difficulties in finding normal hearing persons.The jury generally included students and/or researchers who were not familiar with these kinds of noise signals but had some knowledge of acoustics and sometimes also prior experience in listening tests.Nevertheless, the choice of subjects not familiar with EMM sounds did not limit the reliability of the results.An investigation carried out by the authors to verify whether the experience on the use of these machines could provide additional value in the subjective ratings compared to those by non expert subjects, showed similar results between these two groups (Carletti et al., 2002).
The number of subjects involved in the tests varied form test to test but it was always adequate to ensure the statistical significance of the results.

Preference matrices
The ratings given by each subject for all the pairs of sound stimuli in the listening sequence were arranged in a matrix, called the preference matrix.
In this matrix, the general element x ij (i = row index and j = column index) represented the judgement expressed by the subject referring to the comparison between stimulus i and stimulus j.
When the specific test was carried out according to the classic version, each of these elements could take only the value 0 or the value 1, depending on the preference given by the subject (stimulus j preferred to stimulus i or vice versa).
When the specific test was carried out according to the paired comparison modified version, each matrix element could also take the value 0.5 when the two sound stimuli in the pair were equally rated by the subject.Table 1 shows an example of the preference matrix in the case of a classic paired comparison test involving six sound stimuli (A-F).
Table 1.Preference matrix of a subject for a test involving six sound stimuli (A, B, C, D, E, F) In this matrix the sum by rows gives the preference of each sound stimulus when compared to all the others.Whichever method was applied, the subjective responses of the entire listening jury were arranged in the overall preference matrix which was obtained by adding the scores of the preference matrices of each subject, after the exclusion of the subjects who did not pass the necessary consistency checks explained in the following.

Consistency check of each subject
According to the procedure defined by Kendall and Babington Smith (Kendall & Babington Smith, 1940), in every listening test the consistency for each subject and the agreement among the subjects have to be evaluated in order to "guarantee the control of the variance due to the emotional state of the judging individuals" (Blauert & Jekosch, 1997).
To test for the consistency of each subject, two different checks were carried out in the several experiments: a) the check regarding the number of circular triads in the data set; b) the check regarding the judgement given by the subject to the repeated pair of stimuli.

a) Circular triads
In a paired comparison test involving three signals (A, B, C), the judgements given by a subject on comparisons "AB", "BC" and "AC" can be graphically represented using a triangle, usually called the triad.Under the hypothesis that a subject chooses A in the first comparison between (AB) and B in the second comparison (BC), the choice of C in the third comparison (CA) does not obey the transitive property and therefore identifies an inconsistency which is graphically represented by a circular triad, as shown in figure 2(b).Referring to the investigations relating to loaders, the paired comparison test often involved 6 sound stimuli.The preference matrix for a classic test may be represented either in tabular form (as previously shown in table 1), or may be represented geometrically as in figure 3.This latter method may help in determining the number of circular triads contained in this polygonal representation.In a general test involving n sound stimuli, for each subject the consistency coefficient was calculated on the basis of the number (d) of circular triads found in the complete set of judgements, referred to the maximum number of possible circular triads for that set of n sounds (d max ) (Kendall & Babington Smith, 1940): The value of this coefficient was then compared to its expected value E(K), calculated under the hypothesis that the observed circular triads were normally distributed (see tables in the Kendall and Babington Smith manuscript).Values of K smaller than E(K) corresponded to a data set where a tendency for inconsistent judgements was observed.

b) Repeated pair
One of the easiest ways to check whether people are consistent with their own answers is to ask them to judge the same pair of sound stimuli twice and compare the results.This check was considered successful when the subject gave concordant answers.However, taking into account the high variability in the subjective perception and the possibility that such an inconsistency could be random or unique, the failure of this test was not considered a sufficient condition to consider the subject unreliable and this check was always complemented by the previous test based on the circular triads.

Agreement among several subjects
To test for the agreement among the subjects, the coefficient of agreement was calculated, which takes into account the number of concordant judgements between pairs of subjects (Kendall & Babington Smith, 1940).In a test involving n sound stimuli and m subjects, if x ij is the element (i,j) of the preference matrix, the agreement coefficient is defined as: where S is the total number of agreements between pairs of subjects, derived from the following equation: The statistical significance of u strictly depends on the probability that its value is exclusively a random value.In the several experiments, the probability to obtain a specific value of u, as a function both of the distribution of each subject judgments and of the distribution of the judgments given by all the subjects regarding each specific matrix element was obtained by considering the variable (Kendall & Babington Smith, 1940): This variable follows the  2 distribution, with a number of degrees of freedom given by: 2 (1 ) (1 ) 2( 2) When the modified paired comparison method was applied, a slight different procedure was used to calculate the agreement coefficient u.According to this procedure, each matrix element with value 0.5 has to be excluded from the calculation of the overall judgements and the modified agreement coefficient u m is defined by: where X is the number of the preference matrix elements with value 0.5 and S max is given by: 1 222

The milestones in the investigations referring to loaders
This part of the chapter collects the most significant experimental investigations carried out on compact loaders.The particular interest in this kind of machine is due to the fact that it is widely used.Thanks to its compact size, it goes where bigger machines can not, has a reduced cost, it is easily transportable, agile and productive.Unfortunately, this compactness makes it one of the worst machines as far as the noise emission is concerned, as the operator is very close to the main sources of noise (engine and hydraulics).Consequently, noise and vibration levels at the operator station are extremely high, causing very uncomfortable conditions for workers.

Noise signals and auditory perception of annoyance
This investigation was performed in order to better understand the relationship between the multidimensional characteristics of the noise signals recorded at the operator position in different working conditions and the relevant auditory perception of annoyance (Carletti et al., 2007).
The tests involved six binaural signals recorded at the operator station of three loaders belonging to the families A, B, and C, while these machines were repeating the same work cycle which included two main operations: the loading of the material from a stockpile and the unloading of it in a specific position.In the following these machines will be indicated as A1, B1, and C1 and the different kinds of material as L (loam) and G (gravel).

Objective parameters
Based on the results of a study concerning the sound quality evaluation of wheel loaders (Khan & Dickson, 2002), several acoustic and psychoacoustic parameters were calculated for the left and the right signals, separately.This set included: the overall sound pressure levels L eq and L Aeq (in dB and dBA), the mean values of loudness (in sone), sharpness (in acum), fluctuation strength (in vacil) and roughness (in asper).Referring to the psychoacoustic parameters, they were all calculated according to the models proposed by Fastl and Zwicker (Fastl & Zwicker, 2006).
The results obtained for the six noise signals are summarised in table 2 (columns 3 to 8), while the frequency content of these signals is well described by the sonograms of the sound pressure level shown in figure 4, which refer to the different machines and working conditions.Taking into account that during work the engine rotational speed of these machines ranged from 2000 to 2500 rpm, three interesting frequency intervals can be recognised.
The first one, in the 40-400 Hz frequency range, is directly related to the engine noise (engine rotational frequency, firing frequency and higher orders).
The second one, in the 500-3150 Hz frequency range, is related to the noise generated by the engine cooling system and the hydraulic system, this latter which drives arm, boom and bucket.In particular, at frequencies above 1kHz the noise contribution of the hydraulic system becomes the dominant one.
Finally, the third interval, at frequencies above 4 kHz, is related to the noise generated by the interaction between equipment and material or between various metallic parts of the machine (occurring, for example, when the actuators reach their travel limit).
The difference between these sonograms is significant.At the engine characteristic frequencies the noise levels are higher for A1 than for B1 and C1 while at the hydraulic system characteristic frequencies the opposite occurs.At frequencies above 4 kHz, the noise components are always higher during operations with gravel than with loam, regardless of the machine used.

Subjective evaluations
All the possible pairs of the six binaural signals recorded during the work cycle with gravel and loam were presented to a group of 19 normal-hearing subjects (17 males and 2 females), all non expert subjects, that means without experience in listening tests or in the evaluation of the earth moving machine noise.All tests were performed according to the procedures described in paragraph 3.3.After listening to each pair of sound stimuli as many times as necessary, the subject had to answer to the following question: "Which of the two sounds is more annoying?Sound 1 or Sound 2".No ties were permitted.
All the ratings given by the subjects satisfied the consistency tests and were included in the analysis process.The subjective ratings were arranged in matrices and then the annoyance overall score for each stimulus was obtained in terms of the number of cases it was judged more annoying than all the other ones.This value, normalised to the maximum score that the stimulus itself could have obtained, is reported in the second column of table 2.

Results
As shown in table 2, the C1 machine handling gravel (C1 G ) was the most annoying (99%), whilst the A1 machine handling loam (A1 L ) was rated the least annoying (19%).
Referring to the noise emissions of the machines handling different materials, the overall levels indicated in table 2 and the sonograms in figure 4 show that when the machine is working with loam, the overall noise emission is generally lower than that generated when working with gravel, regardless of the machine characteristics.The loam seems to have a damping effect on the different noise components both when the machine is loading the bucket and when it is transporting the material.
Referring to the different machines, C1 was always judged more annoying than B1, and B1 was always judged more annoying than A1, for each handled material.The annoyance ratings greater for C1 than for B1 could be simply related to the highest noise levels.On the contrary, the annoyance ratings greater for C1 and B1 than for A1 could not be explained in terms of the overall noise levels but in terms of the highest noise levels emitted by B1 and C1 at the characteristic frequencies of the hydraulic system and at frequencies higher than 4 kHz.
The spectral characteristics described above clearly point out the relevance of the noise components at medium and high frequencies in affecting the subjective evaluation of the sound with respect to its annoyance.The subjective ratings of annoyance, however, cannot always be explained taking into account only the energetic characteristics of these signals.
As an example, A1 L (19% annoyance rating) has an overall level higher than that of B1 G (78% annoyance rating), even if the first signal is judged significantly less annoying.This example highlights the absolute necessity to complement this energetic analysis with other considerations involving also the psychoacoustic parameters and their variability over time.
The Pearson correlation coefficients with the annoyance ratings were calculated for all the parameters in table 2. The best correlation was obtained with sharpness (r = 0.94) and relatively high values were also found with loudness (r = 0.87) and L Aeq (r = 0.85).The parameter least correlated with the annoyance ratings was L eq , with r = 0.40.
In addition, for each objective parameter the correlation coefficient between left and right signals was also evaluated.These correlations were consistently very high (almost equal to 1) for all the parameters.For this reason, only the signal with the highest correlation coefficient with respect to the subjective judgements was chosen for analysis.
Referring back to A1 L and B1 G noise signals, the different subjective judgements can be found in the sharpness value or, better, in its time history.Figure 5 shows some percentile values of sharpness for the different machines and materials.The sharpness percentiles of A1 L are significantly lower than those of B1 G .In addition, under working condition with gravel, all the noise signals have very high values of percentile sharpness S 5 with respect to their average sharpness S 50 .As S 5 percentile describes the variability over time of these signals much better than S 50 , the very high values of this parameter underline that prominent noise events occur very frequently under working conditions with gravel and this leads to a negative subjective evaluation.
The good correlation of S 5 with the annoyance ratings (r = 0.91) and the possibility to take into account variability over time of the noise signals makes this parameter very important for acoustic comfort improvement.Moreover, considering that the auditory sensation of this parameter greatly depends on the signal content at medium-high frequencies (Fastl & Zwicker, 2006), the above results gave a further proof of the relevance on the subjective ratings of annoyance of the noise components generated both by the hydraulic system and the handling of materials.This cumulative distribution shows the percentage of time for which a given loudness value (in sone) is not exceeded.The blue line identifies the loudness distribution for the machine working with loam while the red one identifies the loudness distribution for the machine working with gravel.The percentile loudness N 5 can be read at the ordinate point 0.95, N 10 at the ordinate point 0.90 and N 95 at the ordinate point 0.05.These two curves have very different gradient, depending on the working conditions (loam or gravel).The curve with lower gradients (gravel) shows that the loudness values are more evenly distributed over time.On the other hand, the noise recordings of the machine working with gravel have always been judged more annoying than those of the machine working with loam.These results seem to confirm some conclusions of previous studies which illustrated how changes of loudness during the considered time frame may be very important in the judgement of annoyance (Genuit, 2006).

Final remarks on the relevance of this investigation
This study provided some fundamental results for the progress of the investigations.Firstly, how to describe the auditory perception of annoyance by means of some objective parameters.Loudness and sharpness are suitable for this purpose and S 5 can be used to better describe the effects on annoyance of the time variability of the noise components at medium-high frequencies.
Secondly, the relevance on the auditory perception of annoyance both of the noise signals overall energy and the frequency distribution.The 400-5000 Hz frequency range, which includes the noise contributions generated by the hydraulic system and the handling of materials, is the most important referring to the annoyance judgements.
Finally, the absolute relevance of the temporal characteristics of these signals in identifying the relationship between machine characteristics/working conditions and auditory perception of annoyance.

Just noticeable difference in loudness and sharpness
The knowledge of the parameters best correlated to the annoyance sensation is insufficient to develop a methodology able to identify the basic criteria for noise control solutions which guarantee the improvement of the operator comfort conditions.Tiny variations in stimulus magnitude may not lead to a variation in sensation magnitude.In order to detect the step size of the stimulus that leads to a difference in the hearing sensation, the differential threshold or just noticeable difference, JND, should be known for all the parameters of primary interest (Fastl & Zwicker, 2006).JNDs of amplitude and frequency, as well as duration changes of pure/complex tone or broad band noise, have been investigated for decades.Unfortunately, little is known regarding the JNDs of sound quality metrics in real noises (Sato et al., 2007;You & Jeon, 2008).Regarding this a specific investigation was performed by the authors aimed at evaluating the JNDs for the two psychoacoustic parameters describing at best the auditory perception of noise signals at the operator station of compact loaders with respect to the annoyance subjective ratings (loudness and sharpness) (Pedrielli et al., 2008).

Sound stimuli
This investigation involved a binaural noise signal recorded at the operator station of a compact loader of family F in stationary conditions, with the engine running at 2300 rpm.
The recorded signal was post-processed following various steps: generation of a sound stimulus with the same signal at both ears (diotic stimulus), in order to help listeners to concentrate only on the difference between the sounds having different loudness or sharpness, without being influenced by interaural differences; -counterbalance of the spectral modifications that occur during playback, depending on the specific sound card and electrostatic headphones used for the listening tests; creation of sound stimuli with different loudness or sharpness values according to the design of experiments typical of the Method of Limits.For the evaluation of loudness JNDs, the overall sound pressure level of the original sound was varied in order to change the total loudness value by interval steps of +0.3 sone and -0.3 sone.The sharpness value among these stimuli was kept constant.Apart from the original sound, 9 sounds with higher loudness values and 9 with lower loudness values were created.The specific loudness of all these sound stimuli is reported in the left side of figure 7 where the thick line represents the stimulus used as reference in the listening tests.For the evaluation of sharpness JNDs, the original sound was filtered in order to change the sharpness value by interval steps of +0.02 acum and -0.02 acum.This effect was achieved with a 1/3 octave band filter with a negative gain in the 40-80 Hz range and a positive gain in the 4-20 kHz range.The maximum difference in loudness among the stimuli with different sharpness values was less than 0.1 sone.As found in a similar study (You & Jeon, 2008), although concerning a different sound source, such a difference should not influence the responses of subjects with respect to the sharpness feature.Apart from the original sound, 9 sounds with higher sharpness value and 9 with lower sharpness value were created.The 1/3 octave band spectra for the sound pressure level are shown in the right side of figure 7 in order to illustrate the filter effect.

Listening tests
The subjective listening tests were performed following the classical Method of Limits (Gelfand, 1990).According to this method, two stimuli are presented in each trial and the subject is asked whether the second is greater than, less than, or equal to the first with respect to a certain parameter.The first stimulus is held constant (reference stimulus) and the second is varied by the experimenter in specific steps.The procedure is repeated several times in subsequent ascending and descending runs.
In our experiments, a total number of six runs (three ascending alternated to three descending runs) were planned for each loudness and sharpness test.
The entire experiment was divided into three test sessions, different from each other as far as the sound pressure levels of the reference stimulus are concerned.In every test session each subject was asked to perform a test to detect firstly loudness JNDs and then sharpness JNDs.A few minutes' was scheduled between the loudness and sharpness tests.21 subjects (16 males and 5 females) took part in the first and second test sessions, while 16 subjects (12 males and 4 females) took part in the third test session.50% of the listening jury had prior experience in subjective listening tests, but had never experienced this specific psychophysical procedure (Method of Limits).Moreover, 50% of the listening jury was not familiar with the psychoacoustic parameters for which the evaluations were requested (loudness and sharpness).
Table 3 shows the structure of the experiment, also giving information about the metrics of the reference stimulus in each test.3. Reference sound stimuli for all the six tests

Results
At the end of the listening tests, the given judgments by each subject were summarised as shown in figure 8.
Referring to the loudness test, the Method of Limits resulted in a range of values in which the second stimulus was louder than the first (reference), a range in which the second was quieter, and a range in which the two sounds appeared to have an equal loudness value.Similar results were found for sharpness test, where "louder" and "quieter" became "higher " and "lower" sharpness, respectively.The differential threshold (limen) for each subject was estimated once the average upper and lower limens had been defined.The upper limen was halfway between louder/higher and equal judgments, and the lower limen was halfway between quieter/lower and equal judgments.The average limens were obtained by averaging the upper and lower limens across runs.The range between the average upper limen and the average lower limen represents an interval of uncertainty, and the just noticeable difference, or difference limen, is generally estimated as half of this uncertainty interval (Gelfand, 1990).Once the difference limens had been calculated for each subject, some statistical considerations could be outlined for the loudness and sharpness test, separately.

Just noticeable differences in loudness
Table 4 shows the results for the test of just noticeable differences in loudness.In this table, the variation range of the JNDs among the subjects and some percentile values are reported.
The loudness value of the reference stimulus of each test is also specified.The just noticeable difference becomes greater as the overall sound pressure level of the signal increases.This indicates that the greater the level, the more difficult it is for the subject to detect tiny loudness variations in the sounds.

SPL around
Cumulative distributions rather than unique values of just noticeable differences are more functional and make it possible to choose the just noticeable differences value depending on the specific target.For this research, the 75° percentile was considered appropriate.An average or median value would not guarantee that the improvement of the operator comfort conditions were extensively appreciated.Consequently, for loaders where the sound pressure levels at the operator position are around 80 dB, the just noticeable difference in loudness is assessed as 0.8 sone.

Just noticeable differences in sharpness
Table 5 shows the results for the test of just noticeable differences in sharpness.
In this table, the variation range of the JNDs among the subjects and some percentile values are reported.The sharpness value of the reference stimulus of each test is also specified even if, as expected, it is almost independent of the sound pressure level variation.The just noticeable differences show little variations with the presentation level and only for the 90° percentile.Also for this psychoacoustic parameter, the just noticeable difference was defined as the minimum variation in sharpness detected by at least 75% of the jury subjects.Consequently, at the operator station of earth moving machines, the just noticeable difference in sharpness is assessed as 0.04 acum.

Final remarks on the relevance of this investigation
A specific metrics for loudness and sharpness (the two psychoacoustic parameters describing at best the annoyance auditory perception caused by these noise signals) was developed.In order to describe the step size of these parameters that leads to a difference in the hearing sensation of a group of people, a statistical approach was followed.The 75° percentile was considered appropriate; an average or median value, on the contrary, would not guarantee that the improvement of the operator comfort conditions were extensively appreciated.Focusing on the highest presentation level, 75% of subjects perceived a different sensation when sounds had a loudness difference of at least 0.8 sone and a sharpness difference of 0.04 acum.These values were chosen as JND of loudness and sharpness to be used in the other investigations.

Active noise control and sound quality improvement
The effectiveness of the active noise control (ANC) approach to strongly reduce the low frequency noise content has already been shown in many applications involving real and simulated experiments (Fuller, 2002;Hansen, 1997Hansen, , 2005;;Scheuren, 2005).As for the specific field of earth moving machines, only a limited bibliography dealing with the ANC approach is available, despite the significant noise contributions at low frequency.On the other hand, the effectiveness of this approach has been evaluated only in terms of reduction of the overall sound pressure level.Taking into account that the noise level reductions are key elements for worker but they are not always related to improvements in sound quality, a study was carried out aimed at complementing the classical evaluations of such an approach with subjective evaluations of the modifications induced by an ANC system with regard to some noise features important to qualify the comfort and safety conditions (Carletti & Pedrielli, 2009).

The implemented ANC system
All the experiments were carried out on a skid steer loader of family B, equipped with lateral windows and door, in the winter version, as shown in figure 9.In the EMM industry, where the economic constraints are a key element, noise control solutions with a high economic impact associated with the overall cost of the machine are generally not of interest, even if highly technological.Consequently, a cheap and simple single-input single-output system was adopted, with the further limitation that its implementation inside the cab did not require any significant modification in the standard layout of the cab.On the other hand, this choice could be suitable from a technical point of view as inside EMM cabs the volume of interest is very limited and the ANC system must be effective to create a quiet zone only just around the operator's head.
A commercially-available ANC device, following a single channel adaptive feed-forward scheme, was chosen for the tests.This device (1000 Hz sampling frequency) required a reference signal closely related to the primary noise.This synchronism was simply obtained by picking up the impulses from a reflecting strip fixed on the engine shaft of the machine by an optical probe.In such a way the reference signal was not influenced by the control field and the fundamental frequency of the periodic primary noise could be assessed.Based on the reference signal, the ANC device determined the fundamental frequency of the noise, as well as the harmonics to be cancelled.By means of a series of adaptive filters, the output signal was generated and sent to the secondary source.
In order to minimise the economic impact of this implementation, the two loudspeakers of the Hi-Fi system were used as secondary sources.They were fixed to the vertical rods of the cab, at the same height as the operator's head.The error microphone was placed near the operator's head but in such a position that it did not disturb the operator during his work.A low-cost omnidirectional electret condenser microphone with a flat response in the range 40-400 Hz was used.It measured the resulting sound field due to the primary and secondary sources combined.
The control strategy was based on the minimisation of the mean squared value of the sound pressure at the error microphone position (cost function).For this aim, a gradient descendent algorithm was applied in which each controller coefficient was adjusted at each time step in a way that progressively reduced the cost function (filtered-X LMS algorithm) (Nelson & Elliott, 1993).The functional scheme of this ANC system is shown in figure 10.Two more microphones (Mc) were placed near the operator's ears (by using an helmet worn by the operator) in order to monitor the acoustic field in the area of interest, in real time.
Many experiments were carried out in order to both check the capability of this system to reduce the overall sound pressure level in the volume around the operator's head and track any changes due to engine speed variations fast enough to maintain the control.
Table 6 shows the modifications brought on by the ANC system for three different values of the engine rotational speed (1500, 1800 and 2350 rpm); the second column shows the reduction of the noise component at the engine firing frequency (f) and the following two columns show the reduction of the overall levels, linear (L eq ) and A-weighted (L Aeq ), respectively.Table 6.Reductions induced by the ANC system at the engine firing frequency (f), overall sound pressure level (L eq ) and A-weighted overall sound pressure level (L Aeq ) for three rpm values As for the reduction of the overall level, it ranges from 5 to 10 dB and significantly decreases when the engine rotational speed increases: thus the higher the value of rotational speed, the lower the number of tonal components affected by the ANC device.Consequently, a considerable reduction of very few dominant noise components at a low frequency has a small effect on the relevant energetic content of the noise in the frequency range where the system has no influence.This trend is particularly manifest when the effects induced on L Aeq are considered.The reduction of L Aeq is considerably lower than the others (it never exceeds 2 dB) and it turns out to be insignificant at engine speed values higher than 2000 rpm.From a "physical" point of view, the efficiency of this ANC device decreases when the engine rotational speed increases, the minimum efficiency being reached when the engine speed is at its maximum value (2350 rpm).

Subjective evaluation of the ANC system
Binaural noise recordings were carried out at the operator station of this machine, both with the ANC system activated (C, controlled) and with the ANC system not activated (U, uncontrolled) while the loader was operating in stationary idle conditions with the engine running at 2350 rpm.In such a condition, the ANC had the minimum efficiency and the controlled and uncontrolled noise signals had practically the same energy content at middlehigh frequencies but a different distribution of the noise energy at low frequencies, as shown in figure 11.Consequently, subjective tests on controlled and uncontrolled signals would have permitted to check whether this difference, strictly dependent on the ANC action, evoked different subjective reactions despite these two signals had the same L Aeq level.In order to subjectively assess the modifications produced by the ANC system at different levels, both the controlled and uncontrolled sound stimuli were played back at different overall L eq levels, namely 70 dB, 75 dB, and 80 dB.None of these levels actually reproduced the noise at the operator station of the machine (about 20 dB higher).However, these presentation levels were selected mainly to avoid any hazardous hearing effect on the listeners and also because they better highlighted the influence on the auditory perception of specific noise features other than the overall energy content.As for the subjective evaluation of the modifications produced by the ANC system, particularly interesting was the comparison between uncontrolled and controlled sound stimuli with the same linear or A-weighted overall levels.Three pairs of sound stimuli had the same linear overall level: U and C +5 (80 dB); U -5 and C (75 dB); U -10 and C -5 (70 dB).In each of these pairs both the reduction due to the active noise control system at the engine firing frequency and its harmonics went with an increase of the noise content at medium-high frequencies, regardless of the overall level.
Only two pairs of sound stimuli had the same A-weighted overall level: U and C (73 dBA); U -5 and C -5 (68 dBA).In each of these latter pairs the differences are due only to the active noise control system, regardless of the overall level.
The six sound stimuli were arranged in pairs according to the paired comparison procedure and presented to the subjects of the listening jury, tested one at a time.This group of people was formed by eighteen normal-hearing expert operators of earth moving machines, all males aged between twenty-five to fifty years.None of them had previous experience in listening tests but a great experience in using these machines.
After listening to each pair, the subjects were asked to give a rating referring to four different noise features relating to the operator's comfort and working safety conditions: tiredness (T), concentration loss (CL), loudness (L), and booming sensation (B).This rating consisted of a value on a 7-level scale, as shown in figure 12.The meaning of these subjective features was explained to each subject, at the beginning of his listening session.

Results of the subjective evaluations
For each feature, the subjective ratings of the six stimuli were computed by pooling the marks into two categories: significant difference (marks "+++" and "++" added together) and no significant difference (marks "+" and "=" added together).The ratings given by the entire listening jury for the significant difference of each feature are shown in table 9.These ratings were normalised with respect to the maximum score that each stimulus could have obtained and then expressed as percentage values.The grey area of table 9 shows the subjective ratings of "significant difference" obtained for controlled and uncontrolled signals with the same A-weighted overall sound pressure level: U and C (73 dBA); U -5 and C -5 (68 dBA).The reductions in the low frequency noise components brought on by the ANC system positively influenced the subjective evaluations in respect of all the noise features when the controlled and uncontrolled signals had significant differences only at low frequencies, no matter what the playback level.

Features
When the subjective ratings of controlled and uncontrolled stimuli with an equal L eq were considered (U and C +5 (80 dB); U -5 and C (75 dB); U -10 and C -5 (70 dB)), a different behaviour appeared for the four noise features.As far as the T, CL, and L features are concerned, the subjects always judge the controlled signal worse than the uncontrolled one.This accordance holds at all the different presentation levels, even if the higher the level, the greater the subjective difference between controlled and uncontrolled stimuli.Such results show that the subjective ratings are primarily influenced by the energy content of the noise signal at the medium-high frequencies.
Consequently, the effect of an ANC system in respect of the tiredness, concentration loss and loudness features is negatively judged if the reduction of the low frequency components is accompanied by an increase in the components at high frequencies.
When judging the booming feature, an opposite trend can be noticed: the subjective ratings were always positively influenced by the reduction in the low frequency noise components caused by the ANC system, regardless of the content of the signals at medium-high frequency (stimulus U is more booming than stimulus C +5 even if the latter has a higher A-weighted level and then a predominance of the energy content in the medium-high frequency).

Final remarks on the relevance of this investigation
This study showed the feasibility of the ANC approach to improve the sound quality inside loader cabs, provided that the controlled and uncontrolled signals show significant differences only at low frequencies.The sound quality conditions were evaluated by means of subjective evaluations with regards to four different noise features, all related to the operator's comfort and working safety conditions: tiredness (T), concentration loss (CL), loudness (L) and booming sensation (B).
Group 1 10 binaural signals recorded from 5 loaders of family A during the working cycle with loam (L) and gravel (G) Group 2 5 binaural signals from 5 loaders of family A during the simulated work cycle (S) 18.5 18.5 57.0 47.9 13.7 75.9 64.7 86.

Multiple regression analysis
The first six groups of noise stimuli were used to develop the annoyance prediction model while the last three were kept aside to validate it.In order to reach the proposed target, multiple regression analysis was chosen as this technique is the most commonly used for analysing multiple dependence between variables and also because the theory is well developed (Kleinbaum et al., 2007).In this investigation, the Stepwise selection method was firstly applied to each group of noise stimuli in order to identify the smallest set of independent variables which best explained the variation in the subjective annoyance scores (Lindley, 1968).In this respect, the score from subjective listening tests was entered as "dependent variable" and all the objective parameters, considered to be relevant for this investigation, were used as "independent variables".The results obtained for the six groups are shown in table 11.In this table, the parameter R 2 is the square value of the correlation coefficient between the subjective scores and the predicted values of the annoyance.It quantifies the suitability of the fit of the model and shows the proportion of variation in the subjective scores which is explained by the set of the identified parameters.In addition, the Adjusted R 2 values, which takes into account the number of variables and the number of observations, were calculated in order to give a most useful measure of the success of the prediction when applied to real world.

Noise
For each noise group the variables selected by the Stepwise method account for more than 93% of the variation in the subjective scores, with the only exception of group 1.In addition, the set of the physical parameters which represent loudness, sharpness and peak level are very often included in the model, independently from the specific noise group.On the other hand, all the parameters which reflect the same quantity such as N, N 10 , N 50 and N 95 for loudness, or S 5 , S 90 and S 95 for sharpness are strongly correlated among each other.Consequently, in order to identify a common set of predictor variables for each of the six noise groups, further analyses were carried out by substituting some of the parameters shown in table 11 with others reflecting the same acoustic features.The multiple regression analysis was then repeated on the six groups with the "Enter" variable selection method, that is forcing the choice of the set of predictor variables among (Peak, N, S 5 ), (Peak, N, S 90 ), (Peak, N, S 95 ), (Peak, N 10 , S 5 ), ... etc...The set of predictor variables which led to the highest R 2 values for the correlation between predicted and observed annoyance scores was (Peak, N 50 , S 5 ).could provide an alternative and simpler way for manufacturers and customers to assess the grade of annoyance at the workplace of any loader.This model, indeed, intrinsically reflects the main results of the sound quality approach but it is obtained by means of objective parameters only.

Conclusion
This chapter collects the main results of the research performed by the authors in the last five years in order to identify a methodology that is able to establish the basic criteria for noise control solutions which guarantee the improvement of the operator comfort conditions.All the investigations were carried out on compact loaders and permitted to collect the following main results.

Auditory perception of annoyance (see paragraph 4.1)
This study was aimed at better understanding the relationship between the multidimensional characteristics of the noise signals in different working conditions and the relevant auditory perception of annoyance.It highlighted that sharpness and loudness are suitable for this purpose, that the 400-5000 Hz frequency range -which includes the noise contributions generated by the hydraulic system and the handling of materials -is the most important referring to the annoyance judgements and that the temporal characteristics of the signals play an important role.The sharpness fifth percentile S 5 can be used to better describe the effects on annoyance due to the time variability of the noise components at medium-high frequencies.
Just noticeable difference in loudness and sharpness (see paragraph 4.2) This study was aimed at evaluating the minimum differences in loudness and sharpness which are subjectively perceived (just noticeable differences, JND).This information is necessary to develop the specific metrics because tiny variations in stimulus magnitude may not lead to a variation in sensation magnitude.It highlighted that the just noticeable difference in loudness becomes greater as the overall sound pressure level of the signal increases while the just noticeable difference in sharpness has very small variations related to the overall level.Referring to sound stimuli with sound pressure levels around 80 dB, 75% of subjects perceived a different hearing sensation when sounds had a loudness difference of at least 0.8 sone and a sharpness difference of 0.04 acum.This step size was chosen as the JND of loudness and sharpness for all the other investigations.

Effectiveness of an active noise control (see paragraph 4.3)
This study was aimed at verifying the feasibility of a simple active noise control (ANC) architecture.The sound quality conditions were evaluated by means of subjective tests with regards to four different noise features, all related to the operator's comfort and working safety conditions: tiredness, concentration loss, loudness and booming sensation.It highlighted that the effect on the subjective responses of a selective reduction, due to the www.intechopen.comactive noise control system, becomes significant when comparing sounds with the same band levels except for that at the controlled frequency (engine firing frequency, in this case).Therefore in order to improve the operator's comfort and his working safety it would be more effective if the spectral modification produced by an active noise control was associated with a level control in the medium-high frequency range.

Annoyance prediction model (see paragraph 4.4)
This study was aimed at developing a prediction model able to evaluate the grade of annoyance at the workplace of compact loaders by using objective parameters only.This model could provide an alternative and simpler way for manufacturers and customers to assess the grade of annoyance at the workplace of all loaders as it intrinsically reflects the main results of the sound quality approach but it depends on objective parameters only.This model was developed by multi regression analysis thanks to the great amount of the available jury test results and the relevant database of binaural noise signals referred to this k i n d o f m a c h i n e .I t i n c l uded objective parameters Peak, N 50 and S 5 with regression coefficients which best explained the variations of the subjective annoyance scores for all the noise groups used in the developing process.The validation process confirmed a very good correlation between the predicted annoyance values and the subjective ratings resulting from jury tests.Further investigations are in progress, aimed at applying numerical optimisation methods to these noise signals in order to analytically identify the changes in the frequency content which lead to a simultaneous reduction of loudness and sharpness values.As a consequence of the high correlation of these parameters with the subjective perception of annoyance, the noise modifications able to simultaneously reduce these parameters seem to be a promising approach for improving the acoustic comfort at the operator position.The preliminary results of this study have already been published (Carletti et al., 2010b).

Acknowledgment
The work described in this chapter was partially supported by the Laboratory of Research and Technology Transfer LAV (Laboratory of Acoustics and Vibration) realised through the contribution of Regione Emilia Romagna -Assessorato Attività Produttive, Sviluppo Economico, Piano telematico, PRRIITT misura 3.4 azione A -Obiettivo 2.

Fig. 3 .
Fig. 3. Geometrical representation of the scheme of preferences of table 1.

Fig. 5 .
Fig. 5. Sharpness percentile graphs for the different machines and materials handled A deeper insight of the differences in the subjective judgements for machines handling different materials can be obtained by analysing the time-dependent characteristics of the noise signals in terms of loudness distributions.As an example, figure 6 shows the loudness cumulative distribution for machine C1.The same trend, however, could also be obtained for the other machines (A1 and B1).

Fig. 7 .
Fig. 7. Specific loudness of the sound stimuli created for the loudness and sharpness JNDs tests

Fig. 8 .
Fig.8.Judgments given by one subject for the differential thresholds of loudness and sharpness (SPL around 80 dB)

Fig. 9 .
Fig. 9. Skid steer loader used for the implementation of the ANC system

Fig. 10 .
Fig. 10.Layout of the active noise control system.L = loudspeakers, Me = error microphone, Mc = monitoring microphones, FP = photoelectric probe Fig. 11.One-third octave band sound pressure spectra at 2350 rpm with the ANC system on and off 3 65.4 52.1 55.0 30.0 70.0 65.8 29.2 Group 5 10 binaural signals recorded from 5 loaders of family C during the working cycle with loam (L) and gravel (G) Group 6 5 binaural signals from 5 loaders of family C during the simulated work cycle

Table 2 .
Subjective annoyance ratings and acoustic/psychoacoustic parameters

Table 4 .
Just noticeable differences for loudness tests

Table 5 .
Just noticeable differences for sharpness tests

Table 7 .
Table 7 describes the six sound stimuli used in the listening tests.Description of the six sound stimuli used in subjective listening tests

Table 8 .
Table 8 details the description given to the subjects for each feature, aimed at reducing the risk of semantic ambiguity.Description of the four subjective noise features

Table 9 .
Subjective ratings of "significant difference" for the four noise features, in percentage values

Table 11 .
Results of the "Stepwise" selection method applied to the six noise groups

6 Final remarks on the relevance of this investigation
The multiple regression equations for this set of parameters are shown in table 12.The prediction model was developed on the basis of a huge amount of binaural noise signals recorded at the operator position of several families of loaders.Its regression equation :