Improvement of impact noise in a passenger car utilizing sound metric based on wavelet transform

A new sound metric for impact sound is developed based on the continuous wavelet transform (CWT), a useful tool for the analysis of non-stationary signals such as impact noise. Together with new metric, two other conventional sound metrics related to sound modulation and fluctuation are also considered. In all, three sound metrics are employed to develop impact sound quality indexes for several specific impact courses on the road. Impact sounds are evaluated subjectively by 25 jurors. The indexes are verified by comparing the correlation between the index output and results of a subjective evaluation based on a jury test. These indexes are successfully applied to an objective evaluation for improvement of the impact sound quality for cases where some parts of the suspension system of the test car are modified.     

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.     

Sound quality evaluation of vehicle suspension shock absorber rattling noise based on the Wigner–Ville distribution

In this paper, a new sound metric–Sound Metric based on the Wigner–Ville distribution (SMWVD) – was developed to investigate the relationship between subjective evaluations and vehicle suspension shock absorber rattling noise, which substantially affects passengers’ psychological and physiological perceptions. A complete vehicle road test was conducted to measure the interior shock absorber noises, which were subjectively evaluated by 20 jurors. Conventional psychoacoustic indices, i.e. loudness, sharpness, roughness and fluctuation strength, were used to calculate the correlation coefficients between the objective and subjective evaluations, and then, the results were compared with the performance of the SMWVD. The results show that conventional sound metrics have poor relationships with the subjective ratings, while the SMWVD displayed a high correlation of >0.9 between the objective evaluation and the subjective evaluation. These results indicate that the SMWVD can be used to estimate the rattling noise index of a suspension shock absorber without jury evaluation.     

Reliability improvement of a sound quality index for a vehicle HVAC system using a regression and neural network model

The reduction of vehicle interior noise has long been the main interest of noise and vibration harshness (NVH) engineers. A driver’s perception of vehicle noise is largely affected by psychoacoustic noise characteristics and SPL. Among the various types of vehicle interior noise, the sound of the heating, ventilation, and air conditioning (HVAC) systems is a source of distraction for drivers. HVAC noise is not as loud as the overall noise level; however, it affects a driver’s subjective perception and may lead to feelings of nervousness or annoyance. Therefore, vehicle engineers work not only to reduce noise, but also to improve sound quality. In this paper, HVAC noise samples were taken from many types of vehicles. Objective and subjective sound quality (SQ) evaluations were obtained, simple and multiple regression models were generated, and these were used with the Semantic Differential Method (SDM) to determine what characteristics trigger a “pleasant” response from listeners. The regression analysis produced diagnostic statistics and regression estimates. In addition, neural network (NN) models were created using three objective numerical inputs (loudness, sharpness, and roughness) of the SQ metrics and one subjective output (“pleasant”). The NN model was used primarily because human perceptions are very complex and often hard to estimate. The estimation models were compared via correlations between SQ output indices and hearing test results. Results demonstrated that the NN model is most highly correlated with SQ indices, which led to determination of suggested methods for SQ metrics prediction.     

混合动力车型燃油箱晃荡声的时变响度评价方法与降噪应用

随着市场对汽车舒适性要求的提高,燃油箱油液晃动噪声问题越来越被重视。尤其是对于混合动力乘用车型,由于缺少发动机怠速噪声的掩蔽效应,更容易引起市场用户对燃油箱晃荡声的抱怨。本文以某搭载BSG混合动力SUV(Sports Utility Vehicle)车型的燃油箱晃荡声问题为案例,系统性地进行了整车测试分析与路径排查工作,通过对比分析声压级与响度指标方法的差异,说明了采用时变响度声品质指标能够更准确地反映出车内人耳对晃荡声的主观评价感受。本文主要通过“结构声”传递路径的优化,降低了油箱晃动激励到车内的传递,显著改善了车内的油液晃荡声问题,这为提升燃油系统NVH性能集成开发的能力,有着较重要的工程参考价值。     

Sound quality prediction of vehicle interior noise using deep belief networks

The sound quality of vehicle interior noise strongly influences passengers’ psychological and physiological perceptions. To predict the sound quality of interior noise, a vehicle road test with four compact cars has been conducted. All recorded interior noise signals have been denoised via a discrete wavelet transform (DWT) denoising procedure and subsequently evaluated subjectively through the anchor semantic differential (ASD) test by a jury. In addition, a novel prediction method, namely, regression-based deep belief networks (DBNs), which substitute the support vector regression (SVR) layer for the linear softmax classification layer at the top of the general DBN’s structure, has been proposed to predict the interior sound quality. The parameter selection of the DBN model has been compared and studied using a grid search. In addition, four conventional machine-learning-based methods have been introduced to enable a comparison of the performance with the newly developed DBNs. Furthermore, the feature fusion ability of DBNs has been studied by varying the amount of information that the dataset offers. The results show the following: (1) The accuracy and robustness of the proposed DBN-based sound quality prediction approach are better than those of the 4 other referenced methods. (2) The multiple-feature fusing process can strongly affect the prediction performance. (3) Finally, the unsupervised pre-training process of the DBNs can enhance the information fusing ability. Finally, the newly proposed regression-based DBN approach may be extended to address other vehicle noises in the future.     

Monitoring road surfaces by close proximity noise of the tire/road interaction

Applied acoustics is becoming an important field for civil infrastructure and environmental assessment, and road maintenance or rehabilitation strategies. In this research LA(2)IC has developed a GPS-based measurement techniques and apparatus on a test vehicle, for monitoring the acoustical properties of different road pavement surfaces with a reference tire. A field test on PA-12 Spanish porous pavement found in Ciudad Real is developed. The test procedure, a modification based upon the close-proximity method (CPX), relies on the use of three standard microphones situated very close to the tire/road contact patch. This procedure allows the simultaneous measurement of the sound emission synchronized to a GPS receiver, which permits tracking of the position of the sound emission. Geo-referenced sound spectra for every 10 m during individual passes of the test vehicle are analyzed to determine the tire/road noise emissions from tire/PA-12 pavement interaction. Noise levels of around 102 dB(A), with a variability of approximately 0.6 dB(A), are found at a reference vehicle speed of 85 kmh. The frequency spectrum analysis over the test section shows noticeable differences for frequencies above 1 kHz, where the tire/road noise generation mechanisms are dominated by air pumping.     

Using selective intensity and a HATS to evaluate noise sources in a car working at idle

Noise source ranking is required to make the noise level of a vehicle the lowest possible. That implies knowing the noise sources with the highest contribution to the total noise levels.Through the application of coherence techniques, the selective intensity can be defined as the portion of intensity that is coherent with a reference signal. Therefore, it is an effective way to determine the internal root causes of the emitted noise.In this paper, three experiments based on the selective intensity technique have been defined. The objective is observing the contributions of different noise sources of a vehicle, both outside and inside of it, when it is working at idle, and using as reference signals the two microphones of a HATS.With these experiments, it can be evaluated, on the one hand, the coherence between the intensity in the driver’s seat and external microphones located on both sides of the frontal axle of the car, in the exhaust and in the engine. On the other hand, it is evaluated the coherence between sound intensity in the same external points of the car and different positions of a HATS outside and inside of it; thus, as novelties the relation between the noise emitted by different parts of the vehicle and the noise perceived by the vehicle’s driver and by people located outside could be studied.     

Research on the procedure for analyzing the sound quality contribution of sound sources and its application

Transfer path analysis (TPA) plays an important role for identifying and quantifying the contribution by airborne and structure-borne in the automotive industry. The main bottleneck of the TPA method is the test time consumption and complex procedure. It becomes a key target in many applications to find out the source with dominant contribution to overall noise rather than to identify each source. In recent years the contribution pattern of sources to the vehicle overall interior noise has changed with the reduction of engine noise, which masks all other sources. The panel radiation noise of vehicle body could not be ignored. There is an increasing demand for analyzing the sound quality contribution of sound sources in simple ways. The procedure for analyzing sound quality contribution of panel radiation noise is suggested in this study, in which an operational path analysis (OPA) method combined with partial singular value decomposition (PSVD) analysis is applied and sound quality objective assessment is introduced. The experimental research for verifying the procedure is finished, from which the source with largest sound quality contribution is picked up from three sources. For engineering application, the sound quality contributions of panels to the interior noise of a micro commercial vehicle are analyzed by using the procedure. By investigating the contributions of sound sources to each sound quality attribute, the dominant sound source is determined.     

Traffic noise reduction due to the porous road surface

Porous road surfaces reduce road traffic noise. A new method of noise reduction assessment is proposed. The noise generated by a few vehicles was measured two times: on an old surface with the dense asphalt and on a new surface with the porous asphalt. Subjective assessments of drive-by noise suggest that the sound exposure and the road surface coefficient can be used as the acoustical characteristics of a road surface. Their average values, with the average number of vehicles passing the receiver during a day or night, makes it possible to predict the equivalent continuous A-weighted sound pressure level for the new road surface. This is the main objective of this paper.     

Statistical classification of road pavements using near field vehicle rolling noise measurements

Low noise surfaces have been increasingly considered as a viable and cost-effective alternative to acoustical barriers. However, road planners and administrators frequently lack information on the correlation between the type of road surface and the resulting noise emission profile. To address this problem, a method to identify and classify different types of road pavements was developed, whereby near field road noise is analyzed using statistical learning methods. The vehicle rolling sound signal near the tires and close to the road surface was acquired by two microphones in a special arrangement which implements the Close-Proximity method. A set of features, characterizing the properties of the road pavement, was extracted from the corresponding sound profiles. A feature selection method was used to automatically select those that are most relevant in predicting the type of pavement, while reducing the computational cost. A set of different types of road pavement segments were tested and the performance of the classifier was evaluated. Results of pavement classification performed during a road journey are presented on a map, together with geographical data. This procedure leads to a considerable improvement in the quality of road pavement noise data, thereby increasing the accuracy of road traffic noise prediction models.     

Acoustical and fire-retardant properties of jute composite materials

This research aims to study the acoustical and flammability properties of biodegradable and easily disposable natural fibre jute and its composite for noise reduction in house hold appliances, automotive and architectural applications. Acoustical properties of jute fibre and felt (natural rubber latex jute composite) were measured in terms of normal specific sound absorption coefficient and sound transmission loss whereas fire retardant tests included limiting oxygen, flame propagation and smoke density test. The results illustrate that low density jute is a better sound absorber as compared to high density jute material, moreover natural rubber latex jute composite gives higher sound transmission class value than jute felt/cloth. Results were also compared with commercially available synthetic, non-biodegradable, glass fibre which indicates that the noise reduction coefficient value and sound transmission class rating of natural rubber latex jute felt are comparable to that of the popular fibre glass. Fire retardant tests show composite’s high limiting oxygen index value as compared to fibreboard and other natural sound absorbing material, wool, low smoke density rating and low light absorption with respect to fibre glass as well as self fire extinguishing ability.     

Evaluation of the acoustic performance of classrooms in public schools

This paper presents the results of an evaluation of acoustic comfort of classrooms built according to a standard design. Three constructive designs located in the metropolitan area of Curitiba (Brazil) have been evaluated, two schools built under each of these three designs, in a total of six schools. The acoustic quality of the classrooms have been analyzed based on measurements of the reverberation time, sound pressure level inside and outside the classrooms, and sound insulation. Measurements of ambient noise (external and internal) followed the Brazilian Standards NBR 10151 and NBR 10152. Measurement of reverberation time and sound insulation followed the international Standards ISO 140-4, ISO 140-5, ISO 717-1, and ISO 3382. Results (sound insulation and reverberation time) have been compared with reference values found in the Brazilian Standard NBR 1279, and in the Standards ANSI S12.60 and DIN 18041. Results reveal poor acoustical quality of the surveyed classrooms, for all 3 constructive designs studied. The surveyed designs do not meet the guidelines of either the Brazilian Standards or of the International Standards employed as references.     

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.     

A road traffic noise pattern simulation model that includes distributions of vehicle sound power levels

Annoyance, sleep disturbance and other health effects of road traffic noise exposure may be related to both level and number of noise events caused by traffic, not just to energy equivalent measures of exposure. Dynamic traffic noise prediction models that include instantaneous vehicle noise emissions can be used to estimate either of these measures. However, current state-of-the-art vehicle noise emission models typically consider a single emission law for each vehicle category, whereas measurements show that the variation in noise emission between vehicles within the same category can be considerable. It is essential that the influence of vehicles that are producing significantly more (or less) noise than the average vehicle are taken into account in modeling in order to correctly predict the levels and frequency of occurrence of road traffic noise events, and in particular to calculate indicators that characterize these noise events. Here, an approach for predicting instantaneous sound levels caused by road traffic is presented, which takes into account measured distributions of sound power levels produced by individual vehicles. For the setting of a receiver adjacent to a dual-lane road carrying free flow traffic, the effect of this approach on estimated percentile levels and sound event indicators is investigated.     

Acoustical characteristics of water sounds for soundscape enhancement in urban open spaces

The goal of the present study is to characterize water sounds that can be used in urban open spaces to mask road traffic noise. Sounds and visual images of a number of water features located in urban open places were obtained and subsequently analyzed in terms of psychoacoustical metrics and acoustical measures. Laboratory experiments were then conducted to investigate which water sound is appropriate for masking urban noise. The experiments consisted of two sessions: (1) Audio-only condition and (2) combined audio-visual condition. Subjective responses to stimuli were rated through the use of preference scores and 15 adjectives. The results of the experiments revealed that preference scores for the urban soundscape were affected by the acoustical characteristics of water sounds and visual images of water features; Sharpness that was used to explain the spectral envelopes of water sounds was proved to be a dominant factor for urban soundscape perception; and preferences regarding the urban soundscape were significantly related to adjectives describing "freshness" and "calmness."     

A sound quality-based investigation of the HVAC system noise of an automobile model

Using methods and techniques of sound quality engineering, the noise of the heating, ventilation and air-conditioning system (HVAC) of an automobile model was studied. Such noise has a great influence on vehicle acoustical comfort and on overall quality perception of a vehicle. The study was divided into two steps. The first step aimed to identify the most significant attributes that contribute to the perception of similarity or dissimilarity of this kind of noise, using the paired comparison technique and correlation of the results with psychoacoustic models. Loudness, spectral composition and tonality, represented by the psychoacoustic models of loudness, sharpness, tone-to-noise ratio and prominence were found to be the most important dimensions for the perception of similarity and dissimilarity of HVAC-noise.In the second step of the study a model to predict subjective response to HVAC sounds using the semantic differential technique was developed. In particular the perception of annoyance was studied and it is shown that the annoyance caused by the HVAC noise can be satisfactorily described by Zwicker’s stationary loudness model, provided that the HVAC noises do not present tonal components. The loudness model also predicts scores on a quiet/loud scale. Both results confirm the power of the loudness dimension and its model introduced by Zwicker for the overall quality of stationary broadband sounds without slow fluctuations or tonal components. From the annoyance model developed in this study a maximum acceptable loudness level for HVAC-systems can be determined.