Identification of vehicle suspension shock absorber squeak and rattle noise based on wavelet packet transforms and a genetic algorithm-support vector machine

The squeak and rattle (S&R) noise of a vehicle’s suspension shock absorber substantially influences the psychological and physiological perception of passengers. In this paper, a state-of-the-art method, specifically, a genetic algorithm-optimized support vector machine (GA-SVM), which can select the most effective feature subsets and optimize the model’s free parameters, is proposed to identify this specific noise. A vehicular road test and a shock absorber rig test are conducted to investigate the relationship between these features, and then an approach for quantifying the shock absorber S&R noise is given. Pre-processed signals are decomposed through a wavelet packet transform (WPT), and two criteria, namely, the wavelet packet energy (WPE) and wavelet packet sample entropy (WPSE), are introduced as the feature extraction methods. Then, the two extracted feature sets are compared based on this genetic algorithm. Another advanced method, known as the genetic algorithm-optimized back propagation neural network (GA-BPNN), is introduced for comparison to illustrate the superiority of the newly developed GA-SVM model. The result shows that the WPSE can extract more useful features than the WPE and that the GA-SVM is more effective and efficient than the GA-BPNN. The proposed approach could be retrained and extended to address other fault identification problems.     

Relationship between loudness perception and noise indices in Valdivia, Chile

Residents perception of road traffic noise loudness in relation to the measured noise indices close to their dwellings was studied. Percentile distributions of five loudness categories as a function of the Day-Night noise index L_DN were obtained. Hearing sensitivity was considered as a factor in loudness perception. In addition, the prevalence of people’s perception of traffic noise in the “Extremely Loud” loudness category was compared with percentage of people stating that they were “Highly Annoyed” by noise. It is concluded that hearing sensitivity for noise is one of the variables that explains the loudness classification difference in different L_DN index ranges and that the percentages of people “Highly Annoyed” by noise are slightly higher than the percentages obtained in the “Extremely Loud” category of loudness perception.     

A new test track for automotive squeak and rattle (S&R) detection

The perceived quality of interior sounds is of increasing importance in the automotive industry since it is important for the customer perception of vehicle quality. Squeak and rattle (S&R) is a group of intermittent interior noise that reduce the sense of quality dramatically. To identify and solve S&R problems the car manufacturers do both simulations and tests in laboratory of complete vehicles as well as subsystems. As a complement, to laboratory testing and for verification, complete vehicle tests at proving grounds are done. In order to systematically test for vehicle S&R noise at proving grounds there is a need for a new type of test track that in a controlled and repetitive ways excite vehicles at different frequencies. This paper describes such a new test track, called the Frequency Sweep Test Track (FSTT). The test track is based on sweep excitation and improves the precision when detecting and solving S&R issues. Different design considerations such as sweep waveform, frequency range and sweep rate are discussed. The track design is evaluated using a quarter-car model including a tandem ellipsoid tyre model. In a case study a FSTT was built and the excitation of a car was measured. The track excited the expected frequency range and the track operated well in detecting a rattle in the dashboard of an executive production car and at which frequency the rattle occurred.     

Sound quality of low-frequency and car engine noises after active noise control

The ability of active noise control (ANC) systems to achieve a more pleasant sound has been evaluated by means of sound quality analysis of a real multi-channel active noise controller. Recordings of real car engine noises had been carried out using a HeadacousticsTM binaural head simulator seated in a typical car seat, and these signals together with synthesized noise have been actively controlled in an enclosed room.The sound quality study has focused on the estimation of noise quality changes through the evaluation of the sense of comfort. Two methods have been developed: firstly, a predictive method based on psychoacoustic parameters (loudness, roughness, tonality and sharpness); and secondly, a subjective method using a jury test. Both results have been related to the spectral characteristics of the sounds before and after active control.It can be concluded from both analyses that ANC positively affects acoustic comfort. The engine noise mathematical comfort predictor is based on loudness and roughness (two psychoacoustic parameters directly influenced by ANC), and has satisfactorily predicted the improvements in the pleasantness of the sounds. As far as the subjective evaluation method is concerned, the jury test has showed that acoustic comfort is, in most cases, directly related to the sense of quietness. However, ANC has also been assessed negatively by the jury in the cases that it was unable to reduce the loudness, perhaps because of the low amplitudes of the original sounds.Finally, from what has been shown, it can be said that the subjective improvements strongly depends on the attenuation level achieved by the ANC system operation, as well as the spectral characteristics of the sounds before and after control.     

Aircraft noise-monitoring according to ISO 20906: Evaluation of uncertainty derived from the human factors affecting event detection

One of the most important issues in aircraft noise monitoring systems is the correct detection and marking of aircraft sound events through their measurement profiles, as this influences the reported results. In the recent ISO 20906 (unattended monitoring of aircraft sound in the vicinity of airports) this marking task is split into: detection from the sound level time history, classification of probable aircraft sound events, and the concluding identification of aircraft sound events through non-acoustic features.An experiment was designed to evaluate the factors that influence the marking tasks and quantify their contribution to the uncertainty of the reported monitoring results for some specific cases. Several noise time histories, recorded in three different locations affected by flyover noise, were analyzed by practitioners selected according to three different expertise levels. The analysis was carried out considering three types of complementary information: noise recordings, list of aircraft events and no information at all.Five European universities and over 60 participants were involved in this experiment.The results showed that there were no significant differences in the results derived from factors such as the participant’s institution or the expertise of the practitioners. Nonetheless, other factors, like the noise event dynamic range or the type of help used for marking, have a statistically significant influence on the marking tasks. They cause an increase of the uncertainty of the reported monitoring and can lead to changes in the overall results.The experiment showed that, even when there are no classification and identification errors, the detection stage causes uncertainty in the results. The standard uncertainty for detection ranges from 0.3 dB for those acoustic environments where aircraft are clearly detectable to almost 2 dB in more difficult environments.     

Examining the use of a time-varying loudness algorithm for quantifying characteristics of nonlinearly propagated noise (L)

A previous letter by Gee et al. [J. Acoust. Soc. Am. 121, EL1-EL7 (2007)] revealed likely shortcomings in using common, stationary (long-term) spectrum-based measures to quantify the perception of nonlinearly propagated noise. Here, the Glasberg and Moore [J. Audio Eng. Soc. 50, 331-342 (2002)] algorithm for time-varying loudness is investigated. Their short-term loudness, when applied to a shock-containing broadband signal and a phase-randomized signal with equivalent long-term spectrum, does not show a significant difference in loudness between the signals. Further analysis and discussion focus on the possible utility of the instantaneous loudness and the need for additional investigation in this area.     

铝板结构兰姆波阵列瞬时相位包络成像及补偿*

针对板结构中多裂纹缺陷的识别和定位问题,提出了瞬时相位全聚焦成像的包络算法,同时提出了一种基于激励信号脉冲时长的波速补偿方法,通过数值仿真验证补偿后的瞬时相位包络全聚焦成像对多缺陷的识别和定位能力。与幅值全聚焦成像相比,可以有效减小噪声、直达波、端面回波引起的虚像,提高缺陷的识别率。与相位全聚焦成像相比,可以实现缺陷处的单峰值聚焦,更便于缺陷的定位。实验结果表明,所提出的波速补偿瞬时相位包络全聚焦成像在 的铝板上对实现了5个缺陷的成像和定位,其定位的平均误差为12.24 mm。     

空调压缩机噪声测试及其声品质客观参量分析*

针对空调压缩机辐射声场的不同场点噪声声品质的差异,采用心理学声品质参量即响度、尖锐度、总感觉噪度,对压缩机辐射声场的不同场点噪声进行声品质客观参量分析,研究压缩机场点噪声声品质客观参量值变化规律。通过特征响度研究各场点噪声响度在频域的分布,并得出压缩机各场点噪声特征响度峰值所在噪声频带。实验结果表明,对于处在压缩机不同方向上的场点,其噪声声品质客观参量值存在明显差异,但其噪声特征响度峰值却处在相同的噪声频带。研究工作为压缩机全方向降噪提供参考依据也为研究压缩机的噪声声品质探索了一种新思路。     

Sound quality evaluation of the booming sensation for passenger cars

Automotive booming noise due to powertrain occurs when pure or narrow band tones related to the firing frequency of engine and its harmonics excite the passenger cavity, which entails a prominent increase of sound intensity. The booming sensation has been considered as very important to the acoustic comfort of passengers. In this study, a sound quality index which can objectively evaluate the booming sensation was derived. Because of the tonal nature of powertrain booming noise, subjective pitch was employed to find only aurally relevant tonal components which influence booming sensation as well as loudness. Using the empirical data and the frequency difference limen for just-noticeable change of booming sensation obtained from the listening test, an existing pitch extraction algorithm could be modified. The modified pitch model was applied to the interior noises of accelerating passenger cars together with a loudness analysis for representing the objective features of booming feeling. Subjective tests using the magnitude estimation method were conducted to evaluate the degree of booming sensation. Finally, booming strength was proposed for quantifying the booming sensation, which was validated by subjective results. The correlation coefficient between the derived booming strength and the degree of booming sensation obtained by the subjective test was 0.926.     

Traffic background level and signal duration effects on aircraft noise judgment

The effects of traffic background noise on the judged noisiness of aircraft flyover events has been further examined in the study reported here. A series of 72 flyover events were assessed by a jury of 35 observers, during 12 separate listening sessions conducted in a controlled test area designed to simulate typical indoor listening conditions. Each aricraft signal was superimposed on a controlled random traffic background signal having a duration exceeding that of the aircraft event. The primary conclusions reached in this investigation show that the presence of a steady mean traffic background noise can reduce the perceived noisiness of aircraft flyover events, provided that the judgment time available is sufficiently greater than the aircraft event time. For a given peak event level, a reduction in associated background noise of 21 dB(A) is shown to be equivalent subjectively to an increase of 5·5 dB(A) in peak event level, with fixed background conditions. Best linear data regressions were found with an index of the form L₀ + k(L_p ? L₀), where L_p and L₀ are the peak signal and mean background levels, respectively. Although the regressions obtained with the noise pollution index, L_NP, for single event judgments generally showed a lower correlation than the L₀ and (L_p ? L₀) regression variables the score data did show a number of significant trends which are also associated with the L_NP index variations computed for single noise events.     

Index for vehicle acoustical comfort inside a passenger car

Sound quality is among the main factors that influence customers’ preference for choosing good automobile products. It all started more than 10 years ago and grows up so fast due to high competition in the automotive industries. A-weighted noise levels and sound power are usually utilised to measure the noise but they are not adequate to characterise the impact sound inside a car. The most popular approach to determine sound quality of a product is to define an annoyance or specific index, which involves both subjective and objective evaluations. Subjective and objective tests should be studied concurrently in order to determine the sound quality inside a passenger car. This approach is used in this paper to evaluate vehicle comfort index according to most frequently used sound quality metrics, namely; Zwicker loudness, sharpness, roughness and fluctuation strength. As a result researchers of different fields of automotive acoustics investigations can use this index according to the type of road (international road roughness) without any need to perform time-consuming jury tests. The metrics are correlated with jury test results that show which of them and how much has affected the acoustical comfort of the vehicle. The relation between road roughness and vehicle acoustical comfort index is another point of interest in this research.     

Spectral loudness summation for sequences of short noise bursts

Recent loudness data of single noise bursts indicate that spectral loudness summation depends on signal duration. To gain insight into the mechanisms underlying this duration effect, loudness was measured as a function of signal bandwidth centered around 2 kHz for sequences of 10-ms noise bursts at various repetition rates and, for comparison, for single noise bursts of either 10- or 1000-ms duration. The test-signal bandwidth was varied from 200 to 6400 Hz. For the repeated noise bursts, the reference signal had a bandwidth of 400 Hz. For the single noise bursts, data were obtained for two reference bandwidths: 400 and 3200 Hz. In agreement with previous results, the magnitude of spectral loudness summation was larger for the 10-ms than for the 1000-ms noise bursts. The reference bandwidth had no significant effect on the results for the single noise bursts. Up to repetition rates of 50 Hz, the magnitude of spectral loudness summation for the sequences of noise bursts was the same as for the single short noise burst. The data indicate that the mechanism underlying the duration effect in spectral loudness is considerably faster than the time constant of about 100 ms commonly associated with the temporal integration of loudness.     

低频纯音不愉悦感主观评价的实验研究

本文提出分别采用“不愉悦度”和“不愉悦概率”作为衡量低频噪声主观感觉的整体评价指标,并确定出评价等级与相应的计算公式。在此基础上,以人工产生的低频纯音为研究对象,结合“5点4级”评价尺度,采用语义细分法,设计并完成了实验室主观评价实验。分析处理实验数据后发现：（1）“不愉悦度”与“不愉悦概率”两种感觉指标的评价结果之间及其各自所确定的评价等级之间存在较高相关性;（2）A,C及线性声级均可用于衡量低频纯音的不愉悦度,三者的衡量效果基本一致;（3）不同频率低频纯音的不愉悦度随声压级的变化趋势不同。     

Effects of roving level variation on monaural detection with a contralateral cue.

Monaural detection with a contralateral cue (MDCC) was measured with and without a 20-dB overall roving level to determine the contribution of loudness to performance on this task. Psychometric functions were obtained for three normal-hearing subjects as a function of the signal-to-noise ratio for pure-tone and 1/3-oct noiseband signals at 500 and 4000 Hz with a wideband noise masker. At 4000 Hz, the roving level degrades performance for the narrow-band noise signal by about 5.3 dB. In addition, the presence of the contralateral cue degrades performance for both the pure-tone and narrow-band noise signals at 4000 Hz by 3 to 6 dB. At 500 Hz, however, performance is not affected by the roving level, and is improved by 3 to 6 dB by the contralateral cue. These results indicate that loudness is being used as a cue only for detection of the 4000-Hz narrow-band noise.     

Relationships between arithmetic averages of sound pressure level calculated in octave bands and Zwicker’s loudness level

Previously it has been found through a series of psychoacoustical experiments that the arithmetic average of sound pressure level calculated in octave bands is a good estimator of loudness for various kinds of environmental noise. Remarkably, the arithmetic average of sound pressure level in octave bands from 63 Hz to 4 kHz, L_m,1/1(63-4k), strongly correlates with the loudness level specified in ISO 532B, LL(Z), as well as with loudness assessment. To investigate this relationship further, a numerical study has been carried out based on Zwicker’s loudness model. As a result, practical expressions to estimate the loudness levels of general environmental noises from the sound pressure levels in octave bands from 63 Hz or 125 Hz to 4 kHz are proposed.     

Explicit form of an implicit method for inverse force identification

Most existing time domain force identification methods are based on the state space method, which has the disadvantage of large discretization error with a low sampling frequency or a long sampling duration. This work transforms the conventional implicit Newmark-β algorithm into an explicit form for the solution of the Ax=b equations, which is an equivalent transformation, and it exhibits the same characteristics of Newmark-β algorithm as an implicit method. The accuracy of this method for the dynamic force identification is illustrated with two shear-frame buildings and a planar truss structure. Numerical results are compared with reference analytical responses. The new method gives more accurate identified force time histories compared with those from the conventional state space method for multiple sinusoidal and white noise excitations with 10% measurement noise in the responses.     

Manifestation of peripherial coding in the effect of increasing loudness and enhanced discrimination of the intensity of tone bursts before and after tone burst noise

To find the possible reasons for the midlevel elevation of the Weber fraction in intensity discrimination of a tone burst, a comparison was performed for the complementary distributions of spike activity of an ensemble of space nerves, such as the distribution of time instants when spikes occur, the distribution of interspike intervals, and the autocorrelation function. The distribution properties were detected in a poststimulus histogram, an interspike interval histogram, and an autocorrelation histogram—all obtained from the reaction of an ensemble of model space nerves in response to an auditory noise burst–useful tone burst complex. Two configurations were used: in the first, the peak amplitude of the tone burst was varied and the noise amplitude was fixed; in the other, the tone burst amplitude was fixed and the noise amplitude was varied. Noise could precede or follow the tone burst. The noise and tone burst durations, as well as the interval between them, was 4 kHz and corresponded to the characteristic frequencies of the model space nerves. The profiles of all the mentioned histograms had two maxima. The values and the positions of the maxima in the poststimulus histogram corresponded to the amplitudes and mutual time position of the noise and the tone burst. The maximum that occurred in response to the tone burst action could be a basis for the formation of the loudness of the latter (explicit loudness). However, the positions of the maxima in the other two histograms did not depend on the positions of tone bursts and noise in the combinations. The first maximum fell in short intervals and united intervals corresponding to the noise and tone burst durations. The second maximum fell in intervals corresponding to a tone burst delay with respect to noise, and its value was proportional to the noise amplitude or tone burst amplitude that was smaller in the complex. An increase in tone burst or noise amplitudes was caused by nonlinear variations in the two maxima and the ratio between them. The size of the first maximum in the of interspike interval distribution could be the basis for the formation of the loudness of the masked tone burst (implicit loudness), and the size of the second maximum, for the formation of intensity in the periodicity pitch of the complex. The auditory effect of the midlevel enhancement of tone burst loudness could be the result of variations in the implicit tone burst loudness caused by variations in tone-burst or noise intensity. The reason for the enhancement of the Weber fraction could be competitive interaction between such subjective qualities as explicit and implicit tone-burst loudness and the intensity of the periodicity pitch of the complex.     

参数未知的舰船辐射噪声检测方法

舰船辐射噪声的检测方法已有广泛研究,其中线谱特征是检测的重要依据。基于线谱特征的舰船辐射噪声检测方法常需要线谱数目、频率等参数作为检测的先验信息,这些信息不准确或无法确知时,检测方法的性能会受到显著影响。针对实际应用中对于未知舰船无法获得其参数信息的情况,研究基于连续谱谱峰特征的更为一般性的信号存在性检测方法。将窄带信号瞬时频率分析的思想扩展到舰船辐射噪声这类宽带信号,从信号频率与能量分布的角度推导得到宽带信号"瞬时频率"的近似表示式。构建宽带信号的瞬时频率检测器,并对其性能进行理论分析,结果表明该检测器的性能主要受舰船辐射噪声瞬时频率方差以及接收信噪比影响。通过计算机仿真和实际数据对算法的性能进行了验证。