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.     

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.     

Development of a highway traffic noise prediction model that considers various road surface types

A highway traffic noise prediction model has been developed for environmental assessment in South Korea. The model is based on an outdoor sound propagation method and is fully compliant with ISO 9613 and the sound power level (PWL) estimation for a road segment, as suggested in the ASJ Model-1998 that is based on PWLs. Due to that model’s selection of two pavement types, such as asphalt or concrete pavement, an unacceptable traffic noise prediction is made in cases where the road surface is different from that on which the model is based. In order to address this problem, several road surface types are categorized, and the PWL of each surface type is determined and modeled by measuring the noise levels obtained from newly developed methods. An evaluation of the traffic noise prediction model using field measurements finds good agreement between predicted and measured noise levels.     

Prediction of noise inside tracked vehicles

In this paper, numerical simulation has been used to predict the noise inside tracked vehicles. To determine the interaction forces between running track system and the chassis hull of a tracked vehicle, a rigid multi-body tracked vehicle mode, which includes the track moving system, was constructed and simulated using ADAMS software. Finite element (FE) and boundary element (BE) models of the chassis hull of a tracked vehicle were created and adopted to perform the vibro-acoustic analysis. Correlation between the FE and BE models and physical measurements proved sufficiently good that the models could be used to predict the interior noise in a tracked vehicle. The structural frequency dynamic response was determined using the software MSC/NASTRAN. The interior noise was predicted using the software SYSNOISE. The predicted noise levels in a tracked vehicle have been found to be in good agreement with physical measurements.     

节气门全开工况下的车内轰鸣噪声预测*

采用内燃机多体动力学理论提取了某四缸汽油机的燃烧激励和惯性激励,将其加载到某车型的整车有限元模型上预测节气门全开工况下的车内噪声。通过仿真与实验的对比,发现仿真声压级曲线的变化趋势与实验基本一致,并且较好地捕捉到了3300～3700 r/min转速段内的轰鸣噪声,证明了仿真结果的可靠性,为整车开发阶段的节气门全开工况NVH性能预测提供技术参考。     

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.     

Dynamic noise modeling at roundabouts

Modeling spatial and temporal noise variations at roundabouts is a tedious task. Indeed, noise levels are strongly influenced by the complex vehicle interactions taking place at the entries. An accurate modeling of the merging process and its impact on vehicle kinematics, waiting time at the yield signs and queue length dynamics is therefore required. Analytical noise prediction models disregard those impacts since they are based on average flow demand patterns and pre-defined kinematic profiles. The only way to capture all traffic dynamics impacts on noise levels is to combine a traffic simulation tool with noise emission laws and a sound propagation model. Yet, such existing dynamic noise prediction packages fail in representing vehicle interactions when the roundabout is congested and are difficult to calibrate due to their numerous parameters. A new traffic simulation tool, specifically developed for roundabouts, is therefore proposed in this paper. It has few easy-to-calibrate parameters and can be readily combined with noise emission and propagation laws. The obtained noise package is able to produce relevant dynamic noise contour maps which can support noise emission assessment of local traffic management policies. Results are validated against empirical data collected on a French suburban roundabout on two different peak periods.     

Fast prediction of aerodynamic noise induced by the flow around a cylinder based on deep neural network

Accurate and fast prediction of aerodynamic noise has always been a research hotspot in fluid mechanics and aeroacoustics. The conventional prediction methods based on numerical simulation often demand huge computational resources, which are difficult to balance between accuracy and efficiency. Here, we present a data-driven deep neural network (DNN) method to realize fast aerodynamic noise prediction while maintaining accuracy. The proposed deep learning method can predict the spatial distributions of aerodynamic noise information under different working conditions. Based on the large eddy simulation turbulence model and the Ffowcs Williams-Hawkings acoustic analogy theory, a dataset composed of 1216 samples is established. With reference to the deep learning method, a DNN framework is proposed to map the relationship between spatial coordinates, inlet velocity and overall sound pressure level. The root-mean-square-errors of prediction are below 0.82 dB in the test dataset, and the directivity of aerodynamic noise predicted by the DNN framework are basically consistent with the numerical simulation. This work paves a novel way for fast prediction of aerodynamic noise with high accuracy and has application potential in acoustic field prediction.     

基于退化数据和DBN算法的IGBT健康参数预测方法

绝缘栅双极型晶体管(IGBT)等电子元器件被广泛用于运输和能源部门,其健康状态对于设备安全和有效至关重要;在对IGBT的结构和损伤机制分析基础上,结合NASA艾姆斯中心开展的IGBT加速退化试验,选择集电极-发射极关断峰值电压作为失效特征参数,提出了一种基于深度信念网络的预测模型对其进行分析和预测;以Levenberg-Marquardt(LM)算法模型作为对比,实验结果显示文章提出的三隐藏层DBN模型相比于LM模型有更好的预测性能和更高的预测精度。     

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.     

利用卷积网络的高速列车主观声品质预测

随着高速列车在中国的高速发展,乘客对舒适性的要求不断提高。因此高速列车内声学舒适性是一个需要研究和解决的问题。首先,该文基于声学人工头设备,获取了高速列车行驶在350 km/h速度下不同车厢、不同区域的双耳噪声样本,并对其分别开展了主观声学评价和基于响度、尖锐度、粗糙度和抖动度等参数的客观声品质分析。结果表明,350 km/h速度下高速列车车内噪声能量集中在3000 Hz以内,风挡区域是舒适性评价较差的位置,而响度是影响主观评价最大的因素。其次,利用卷积神经网络算法将主观评价结果与高速列车噪声样本相关联,建立了车内噪声主观声品质预测模型,并与基于BP神经网络的预测模型进行了对比。结果表明,基于卷积神经网络的主观声品质预测模型具有更高的预测精度,更适宜用于指导高速列车车内声学舒适性的优化设计。     

Modeling of offshore pile driving noise using a semi-analytical variational formulation

Underwater noise radiated from offshore pile driving got much attention in recent years due to its threat to the marine environment. This study develops a three-dimensional semi-analytical method, in which the pile is modeled as an elastic thin cylindrical shell, to predict vibration and underwater acoustic radiation caused by hammer impact. The cylindrical shell, subject to the Reissner–Naghdi’s thin shell theory, is decomposed uniformly into shell segments whose motion is governed by a variational equation. The sound pressures in both exterior and interior fluid fields are expanded as analytical functions in frequency domain. The soil is modeled as uncoupled springs and dashpots distributed in three directions. The sound propagation characteristics are investigated based on the dispersion curves. The case study of a model subject to a non-axisymmetric force demonstrates that the radiated sound pressure has dependence on circumferential angle. The case study including an anvil shows that the presence of the anvil tends to lower the frequencies and the amplitudes of the peaks of sound pressure spectrum. A comparison to the measured data shows that the model is capable of predicting the pile driving noise quantitatively. This mechanical model can be used to predict underwater noise of piling and explore potential noise reduction measures to protect marine animals.     

Application of frequency-domain linearized Euler solutions to the prediction of aft fan tones and comparison with experimental measurements on model scale turbofan exhaust nozzles

Although it is widely accepted that aircraft noise needs to be further reduced, there is an equally important, on-going requirement to accurately predict the strengths of all the different aircraft noise sources, not only to ensure that a new aircraft is certifiable and can meet the ever more stringent local airport noise rules but also to prioritize and apply appropriate noise source reduction technologies at the design stage. As the bypass ratio of aircraft engines is increased - in order to reduce fuel consumption, emissions and jet mixing noise - the fan noise that radiates from the bypass exhaust nozzle is becoming one of the loudest engine sources, despite the large areas of acoustically absorptive treatment in the bypass duct. This paper addresses this ‘aft fan’ noise source, in particular the prediction of the propagation of fan noise through the bypass exhaust nozzle/jet exhaust flow and radiation out to the far-field observer. The proposed prediction method is equally applicable to fan tone and fan broadband noise (and also turbine and core noise) but here the method is validated with measured test data using simulated fan tones. The measured data had been previously acquired on two model scale turbofan engine exhausts with bypass and heated core flows typical of those found in a modern high bypass engine, but under static conditions (i.e. no flight simulation). The prediction method is based on frequency-domain solutions of the linearized Euler equations in conjunction with perfectly matched layer equations at the inlet and far-field boundaries using high-order finite differences. The discrete system of equations is inverted by the parallel sparse solver MUMPS. Far-field predictions are carried out by integrating Kirchhoff's formula in frequency domain. In addition to the acoustic modes excited and radiated, some non-acoustic waves within the cold stream-ambient shear layer are also captured by the computations at some flow and excitation frequencies. By extracting phase speed information from the near-field pressure solution, these non-acoustic waves are shown to be convective Kelvin-Helmholtz instability waves. Strouhal numbers computed along the shear layer, based on the local momentum thickness also confirm this in accordance with Michalke's instability criterion for incompressible round jets with a similar shear layer profile. Comparisons of the computed far-field results with the measured acoustic data reveal that, in general, the solver predicts the peak sound levels well when the farfield is dominated by the in-duct target mode (the target mode being the one specified to the in-duct mode generator). Calculations also show that the agreement can be considerably improved when the non-target modes are also included, despite their low in-duct levels. This is due to the fact that each duct mode has its own distinct directionality and a non-target low level mode may become dominant at angles where the higher-level target mode is directionally weak. The overall agreement between the computations and experiment strongly suggests that, at least for the range of mean flows and acoustic conditions considered, the physical aeroacoustic radiation processes are fully captured through the frequency-domain solutions to the linearized Euler equations and hence this could form the basis of a reliable aircraft noise prediction method.     

Prediction of the attenuation of a filtered custom earplug

A method has been developed to predict the attenuation of an earplug when filtered by passive resistive elements (dampers). The method is based on the assumption that sound transmission paths traveling through the damper element and through the earplug are independent, hence their respective sound energies simply add to each other. This hypothesis was validated with measurements on both an acoustical test fixture and on human subjects, using a commercially available expandable custom earplug. This earplug features a sound-bore that can either be used for an F-MIRE (Field microphone-in-real-ear) attenuation measurement or be fitted with a damper in order to adapt the amount of attenuation to the wearer’s needs. The uncertainty associated with the proposed prediction method was formulated and quantified using REAT and F-MIRE attenuation measurements on human subjects. An initial experimental verification of the prediction method, on a limited number of subjects, has been successfully completed.     

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.     

Experimental and numerical study on aeroacoustic sound of axial flow fan in room air conditioner

Fan is one of the main noise sources of the room air-conditioners. Axial flow fans are widely used in the outdoor unit of split type air-conditioners. The interaction between the fan and the heat exchanger should be taken into consideration. However, only a few researches have been carried out on predicting the aeroacoustic noise because of the difficulty in obtaining detailed information of the flow field. This paper is to understand the generation mechanism of sound and to develop a prediction method for the flow field and the acoustic pressure field of the outdoor unit. Acoustic measurement is performed in a semi-anechoic chamber. Effects of each components is analyzed. Based on commercial computational fluid dynamics (CFD) code, Fluent, Fukano’s model is used to predict the overall sound pressure level of broadband noise. The predicted sound pressure levels based on original Fukano’s model are 7.66 dB and 7.42 dB lower than measurement results at 780 rpm and 684 rpm, respectively. And the errors are about 13%. However, when wake width and relative velocity are both calculated by numerical simulations and the distance to blade trailing edge is taken into consideration, the difference of sound pressure level between measurement and prediction is less than 3.4 dB and errors less than 5.5% while the distance is less than 10 mm. Thus, the distance to blade trailing edge should also be an important parameter for Fukano’s model. In comparison with experimental results, it is clearly shown that the Fukano method based on numerical simulation can provide more accuracy than the original Fukano model and numerical results are in a reliable level.     

燃料电池有轨电车声学优化*

基于线路噪声实验,系统测试分析了燃料电池有轨电车的噪声特性,研究了噪声分布以及空气传声、结构传声路径对噪声的贡献。结果表明改善车辆地板、空调、顶板和风挡的隔声性能,尤其是在500～1250 Hz的1/3倍频带范围内的隔声性能将有助于改善车辆内部声学环境。优化燃料电池系统控制,降低冷却单元转速将有助于改善车辆外部声学环境。在此基础上提出减震降噪建议措施,再次进行线路噪声实验,结果表明该措施有效。     

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.     

Estimation of directivity and sound power levels emitted by aircrafts during taxiing, for outdoor noise prediction purpose

Integrated noise model (INM) is the most internationally used software to calculate noise levels near airports. Take off, landing or pass by operations can be modeled by INM, but it does not consider aircrafts taxiing, which, in some cases, can be important to accurately evaluate and reduce airports’ noise assessment.Aircraft taxiing noise emission can be predicted using other prediction tools based on standards that describe sound attenuation during propagation outdoors. But these tools require data inputs that are not known: directivity and sound power levels emitted by aircraft during taxiing.This paper describes methods used to calculate directivity indexes and sound power levels, based on field measurements made in Madrid-Barajas Airport (Spain). Obtained results can be used as inputs for general purpose outdoor sound prediction software, which will be able to evaluate noise at airports vicinity as industrial noise.Directivity and sound power levels have been estimated in octave and third octave band terms, for several aircraft families.     

Automotive panel noise contribution modeling based on finite element and measured structural-acoustic spectra

The radiated noise contributions of automotive body panels to the interior sound pressure levels are modeled using an approximate spectral formulation that applies the theoretical interior acoustic sensitivity terms derived from a finite element model and measured spatial-averaged structural-acoustic spectra. The finite element calculation is validated by comparison to a set of experimental acoustic transfer functions. A measurement set-up for the sound intensity and structural-acoustic response is applied to acquire the cross and auto power spectra needed to predict the relative mean-squared velocity term of each control plane near the panel surface, and to obtain the individual panel contribution function. The proposed approach also computes the noise spectra in 1/12 octave band form at selected positions in the passenger compartment, which matches well with the overall experimental results. Through an actual passenger car application, the approximate computational scheme is proven to be generally quite robust and effective for analyzing higher frequency interior noise problems.