考虑听觉主观性的封闭空间结构声有源控制

提出一种考虑人耳听觉主观性的结构声有源控制.将响度滤波器集成入控制系统,适当衰减人耳不敏感频率成分以及放大敏感成分,使系统控制目标从声压转变成响度.给出响度滤波器设计和选择的方法,导出结构声有源控制Loudness-LMS控制算法,并应用于矩形封闭空间的有源力控制消声.仿真控制结果表明:与声压控制相比,响度控制具有更好的主观听觉效果.     

听觉频带声能量对车内声品质客观评价影响研究

响度、尖锐度等心理声学客观参量常作为声学特征建立车辆噪声品质客观评价模型。考虑人耳听觉多频带滤波特性,研究听觉频带声能量对声品质客观评价的影响。建立基于频带声能量的汽车车内噪声品质客观量化模型,提高声品质识别的精度和稳定性。采集汽车匀速车内噪声并进行综合烦躁度主观评价试验,建立小波包耳蜗滤波器组提取听觉特征频带内声能量,利用支持向量机建立频带能量与主观评价结果之间的回归模型。交叉验证结果表明,相比于建立的基于心理声学客观参量综合烦躁度模型,建立的人耳听觉特征频带能量综合烦躁度客观评价模型预测的误差均值和误差方差更小,车内噪声品质评价的精度、稳定性均有提高。     

采用听觉传感策略的声品质主动控制

针对现有声品质主动控制多以心理声学参数为控制目标,声品质改善能力不足,提出一种基于听觉传感策略的声品质主动控制系统。为了使控制系统能够融入听觉非线性特性,建立了包括外/中耳模型和内耳模型的听觉传感模型,其中在基底膜建模时,考虑毛细胞对基底膜具有反馈运动调节作用,采用带宽时变的gammatone滤波器模型,该滤波器可模拟出听觉在频率和强度感知方面的非线性特性。然后,以听觉信号平方最小为控制目标,给出了基于听觉传感的主动控制系统结构,为了解决听觉传感环节的加入带来的算法计算量增加和收敛性变差问题,基于x滤波最小均方（Filtered-x least mean square,FLMS）算法,提出了延迟补偿结构与逆模型结构相结合的听觉控制算法。最后,以车速50km/h的汽车车内声为对象进行主动控制仿真,对控制前后的车内声进行了声品质客观与主观评价,并对评价结果进行比较与分析,主客观评价一致表明：与声压控制相比,听觉控制可以更好地改善听觉舒适性。     

基于声信号人耳听觉谱特征的风机故障诊断

提出了风机噪声信号的人耳听觉谱特征提取方法,利用人耳听觉谱特征模拟人耳听觉系统的特性,采用支持向量机分类器进行风机故障的分类识别;设计了基于听觉原理和支持向量机分类器的风机故障诊断系统,并应用于风机故障诊断.文中所用实验数据是在工厂现场采集获得,对现场实测数据的识别实验证明,人耳听觉谱特征可有效用于风机故障诊断,可正确识别99.18%的正常机器,故障类型诊断的正确识别率在91%以上.     

一种低复杂度快速收敛的窄带主动噪声控制系统

传统窄带主动噪声控制( ANC)系统的计算负荷与窄带噪声频带数量正相关,而且其收敛速度和降噪效果存在此消彼 长的关系。 为解决以上问题,首先基于滤波误差技术简化窄带 ANC 模型,使系统计算量与窄带噪声频带数量相互独立。 然后 通过自适应混合参数将两个简化的窄带 ANC 系统进行并行凸组合,其中一个系统拥有最快的收敛速度,另一个系统拥有较低 的稳态误差。 提出的系统不仅降低了传统窄带 ANC 系统的计算复杂度,而且在不牺牲降噪性能的情况下提升了系统收敛速 度。 实验结果表明,提出系统在不牺牲稳态误差的基础上,收敛时间缩短了 78% ,有效提升了系统收敛性能。     

基于噪声主动控制方法的非稳态车内声品质优化研究

首先对16辆各种型号的轿车进行了加速条件下车内噪声样本的采集,通过噪声信号的主客观分析研究,得出主观评价结果与客观物理参量之间的相关性,明确了加速状态下响度、尖锐度及粗糙度是影响车内声品质的主要因素。而后,对声品质最差的7号车运用噪声主动控制方法进行车内噪声优化实验,通过对比发现,车内噪声的响度、尖锐度及粗糙度都有明显的减少。将数据代入声品质客观计算模型,同时进行主观评价实验,结果表明其评分等级从16级降至12级,从而证明了噪声主动控制方法能有效提高加速条件下车内噪声的声品质。     

重卡驾驶室的声学灵敏度分析

车身的声学灵敏度是指施加于车身的单位力在车内产生的声压,是衡量车辆NVH特性的一种很有效的指标。以某重卡驾驶室为研究对象,建立了其声固耦合系统的有限元模型,通过对驾驶室悬置点施加单位激励,绘制了人耳旁的声压响应曲线图,获得一些驾驶室的结构一声学特性。     

基于听觉特性和过零点间隔的多声源定位算法

针对目前声源定位技术的研究现状,研究了人耳听觉系统的生理学和心理学特性,建立了基于人耳听觉系统的多声源定位模型;通过研究信号部分频率成分间的过零点时间间隔与原信号保持一致的特性,提出了用上升过零点模拟听神经的发放行为,从而引入了根据两通道间过零点时间间隔统计特征确定两耳时延的算法,并给出了噪声对时延结果影响的判定方法;相比互相关算法,该算法的计算量较小而抗噪声能力更强,声源的增多不会明显降低定位效果;通过与常用的互相关时延算法对比,仿真实验验证了该算法在较低信噪比情况下,依然可以对多个声源取得较好的定位效果。     

车门关门声品质控制的主观评价体系研究

以客观评价参数响度、尖锐度和振颤度为基础,建立了一套多层次车门关门声品质主观评价体系。基于建立的主观评价体系开展了某轿车车门关门声品质评价及优化控制分析,并通过客观试验法验证了主观评价控制效果。研究表明:建立的主观评价体系可行性较高,可较为快捷地分析和控制车门关门声品质问题,且控制效果明显。该技术对于新车型车门声品质的研发而言,具有较强的工程应用价值。     

基于GA-BP模型的消声器声品质预测与控制技术研究

采用成对比较法的主观评价方法对车辆稳态与非稳态排气噪声进行主观试验,基于排气噪声频谱分析出的响度、尖锐度、粗糙度等心里声学客观参量,用遗传算法优化神经网络模型建立了排气噪声客观参量与主观满意度之间的非线性映射关系,训练拟合R值达到0.994,验证样本误差在5%以内。并将所建立的GA-BP模型应用于消声器的声品质提高设计中,探寻影响消声器声品质结构参数并加以控制,排气声品质满意度提高了16%,所建立模型可以用于预测指导汽车排气声品质的改善,通过控制消声器参数可实现消声器设计阶段声品质可控的目的。     

Active noise control using a distributed mode flat panel loudspeaker

A flat panel distributed mode loudspeaker (DML) has many advantages over traditional cone speakers in terms of its weight, size, and durability. However, its frequency response is uneven and complex, thus bringing its suitability for active noise control (ANC) under question. This paper presents experimental results demonstrating the effective use of panel DML speakers in an ANC application. Both feedback and feedforward control techniques are considered. Effective feedback control with a flat panel speaker could open up a whole range of new noise control applications and has many advantages over feedforward control. The paper develops a new control algorithm to attenuate tonal noise of a known frequency by feedback control. However, due to the uneven response of the speakers, feedback control is found to be only moderately effective even for this narrow-band application. Feedforward control proves to be most capable for the flat panel speaker. Using feedforward control, the sound pressure level can be significantly reduced in close proximity to an error microphone. The paper demonstrates an interesting application of the flat panel in which the panel is placed in the path of sound and effectively used to block sound transmission using feedforward control. This is a new approach to active noise control enabled by the use of flat panels and can be used to prevent sound from entering into an enclosure in the first place rather than the traditional approach of attempting to cancel sound after it enters the enclosure.     

Quiet zone tuning in a non-ideal sound field

Most active noise control (ANC) systems are designed and analyzed in ideal sound fields, where ANC performances are predictable with acceptable accuracies. In many ANC applications sound fields are non-ideal with significant differences between real ANC performances and theoretical predictions. If one uses an ideal model to optimize locations of actuators or error sensors for an ANC system in a non-ideal sound field, the actual quiet zone is inevitably different from its theoretical prediction. It is desired that users of ANC systems can tune quiet zones by adjusting ANC configurations, such as locations of secondary sources or error sensors. Model-independent ANC (MIANC) systems are preferred for this purpose. In this study, a model-independent ANC system is improved, implemented and applied to create a quiet zone in a non-ideal sound field. Users of the system can adjust locations of actuators or error sensors to tradeoff between sizes of quiet zones and levels of noise attenuations. Experimental results are presented to demonstrate observations and effects of quiet zone tuning using the improved ANC system.     

Modified-filtered-u LMS algorithm for active noise control and its application to a short acoustic duct

This paper presents a new adaptive algorithm for active noise control (ANC) that can be effectively applicable to a short acoustic duct, such as the intake system of an automobile engine, where the stability and fast convergence of the ANC system is particularly important. The new algorithm, called the modified-filtered-u LMS algorithm (MFU-LMS), is developed based on the recursive filtered-u LMS algorithm (FU-LMS) incorporating the simple hyper-stable adaptive recursive filter (SHARF) to ensure the control stability and the variable step size to enhance the convergence rate. The MFU-LMS algorithm is implemented by purely experimental ways, and is applied to active control of noise in a short acoustic duct, and is validated using two experimental cases of which the primary noise sources are a sinusoidal signal embedded in white noise and a chirp signal. The experimental results demonstrate that the proposed MFU-LMS algorithm gives a considerably better performance than other conventional algorithms, such as the filtered-x LMS (FX-LMS) and the FU-LMS algorithms.     

基于双DSP的噪声模拟试验系统研究

针对多参数复合环境试验系统中噪声环境的生成要求,提出了一种以双数字信号处理器(DSP)为核心的噪声环境模拟系统的控制结构.该系统与上位机通讯采用异步串口,DSP之间传输数据或命令采用同步串口.在对模糊PID算法进行深入分析和研究的基础上,利用该控制算法对测量噪声信号进行了频域控制,从而实现了噪声模拟系统的闭环自动控制....     

基于GA-BP的汽车风振噪声声品质预测模型

目前对于汽车风振噪声的优化研究主要以声压级（Sound pressure level,SPL）作为单一评价指标,既不能全面反映噪声的物理属性,也无法考虑人耳对噪声的主观认知过程。为准确评价风振噪声,引入声品质,运用大涡模拟（Large eddy simulation,LES）对风振噪声进行数值仿真,根据实车道路试验判断仿真的准确性;对仿真结果进行声品质客观评价与主观评价,综合声品质客观评价参数与声品质主观评价试验结果建立BP神经网络预测模型;利用遗传算法（Genetic algorithm,GA）,进一步对BP神经网络的结构参数进行优化,建立GA-BP声品质预测模型。研究结果表明,GA-BP声品质预测模型在训练速度和预测精度上都优于BP神经网络预测模型。预测模型基于声品质主客观评价结果,其预测值可以代替传统的声压级评价指标,为风振噪声提供更为准确合理的评价。     

The analysis of structural-acoustic coupling of an enclosure using Green’s function method

Currently researchers expect to control the internal noise of an enclosure by controlling the relative structural vibration. The method is called ANC (Active Noise Control). Sound pressure response and velocity response of the structure are two significant factors to evaluate the performance of the ANC. But previous researches have to depend on a three-dimensional model with regular shape. Based on the Green’s function theorem this paper proposed two formulas to describe the contributions of acoustic modes and structural modes. These two formulas are the essential basis for the analysis of structural-acoustic coupling of an enclosure. From them compact matrix formulas are deduced and a numerical simulation method is presented to calculate the responses of sound pressure and velocity. The numerical simulation method is verified by comparing the numerical result with the theoretical one based on a regular model. And the application of the method in an irregular model shows this method can be used to analyze any model with arbitrary shape.     

Design of new sound metric and its application for quantification of an axle gear whine sound by utilizing artificial neural network

The gear whine sound of an axle system is one of the most important sound qualities in a sport utility vehicle (SUV). Previous work has shown that, because of masking effects, it is difficult to evaluate the gear whine sound objectively by using only the A-weighted sound pressure level. In this paper, a new objective evaluation method for this sound was developed by using new sound metrics, which are developed based on the increment of signal to noise ration and the psychoacoustic parameters in the paper, and the artificial neural network (ANN) used for the modeling of the correlation between objective and subjective evaluation. This model developed by using ANN was applied to the objective evaluation of the axle-gear whine sound for real SUVs and the output of the model was compared with subjective evaluation. The results indicate a good correlation of over 90 percent between the subjective and objective evaluations. This paper was recommended for publication in revised form by Associate Editor Yeon June Kang Professor Sang-Kwon Lee received a Ph.D. degree in ISVR (Institute of Sound and Vibration Research) from Southampton University in 1998. He joined Hyundai Motor Research Center in Korea, working with the Automotive Noise and Vibration Control Group from 1985 to 1994. He has been the Professor at the Department of Mechanical Engineering, Inha University, Inchon, Korea, since March 1999. His research interests are the digital signal processing, NVH (noise vibration harahness), condition monitoring, product sound quality design and active control.     

A study on energy saving algorithm of electro-pneumatic regulator with modified PWM driven method

The development of an accurate and energy saving electro-pneumatic regulator that may be applied to a variety of practical pressure control applications is described in this paper. A novel modified pulse width modulation (MPWM) valve pulsing algorithm allows the electro-pneu-matic regulator to become energy saving system. A comparison between the system response of conventional PWM algorithm and that of the modified PWM (MPWM) algorithm shows that the control performance is almost the same, but energy saving is greatly improved by adopting this new MPWM algorithm. The effectiveness of the proposed control algorithm is demonstrated through experiments with various reference trajectories.