基于心里声学客观参量的GA-BP声品质预测模型能够准确的预测稳态排气噪声声品质。对于非稳态噪声研究,引入正则化非稳态回归技术(RNR)优化计算维格纳-威尔分布(WVD)的时频方法,建立新的声品质参量SQP-RW(Sound Quality Parameter Base o...基于心里声学客观参量的GA-BP声品质预测模型能够准确的预测稳态排气噪声声品质。对于非稳态噪声研究,引入正则化非稳态回归技术(RNR)优化计算维格纳-威尔分布(WVD)的时频方法,建立新的声品质参量SQP-RW(Sound Quality Parameter Base on RNR-WVD),用此参量替换掉与满意度相关性较小的客观参量。同时,以Morlet小波基函数作为隐含层结点的传递函数构建小波神经网络(Wavelet Neural Network,WNN),并用GA优化小波神经网络层间的权值和阈值,构造出GA-WNN并用于非稳态排气噪声声品质预测。结果表明:GA-WNN在非稳态排气噪声声品质预测上比GA-BP神经网络更加准确;引入SQP-RW参量,模型具有更高的精度,更能体现出非稳态信号特征及声品质特点。展开更多
车身板面贡献量分析作为研究车身振动对车内噪声影响的重要内容,常用声学传递向量(acoustic transfer vector,ATV)仿真计算来实现。为了进一步探究车身振动对车内语音清晰度的影响,通过对语音清晰度客观参量与主观评价分值的比较,确定...车身板面贡献量分析作为研究车身振动对车内噪声影响的重要内容,常用声学传递向量(acoustic transfer vector,ATV)仿真计算来实现。为了进一步探究车身振动对车内语音清晰度的影响,通过对语音清晰度客观参量与主观评价分值的比较,确定以非稳态加速工况下的语言可懂度指数(speech intelligibility index,SII)为指标,运用ATV仿真手段找出对语音清晰度影响最大的面板。分析结果显示车身顶棚面板对语音清晰度影响最大。针对分析结果,采用遗传算法搜寻和ATV逆运算仿真相结合的方法,有针对性地进行了车身顶棚阻尼敷设并加以验证。结果表明,基于语音清晰度车身板面贡献情况的优化设计,有效地改善了非稳态全油门加速工况下的车内语音清晰程度,提高了车内声音品质。展开更多
The dynamic responses of suspension system of a vehicle travelling at varying speeds are generally nonstationary random processes,and the non-stationary random analysis has become an important and complex problem in v...The dynamic responses of suspension system of a vehicle travelling at varying speeds are generally nonstationary random processes,and the non-stationary random analysis has become an important and complex problem in vehicle ride dynamics in the past few years.This paper proposes a new concept,called dynamic frequency domain(DFD),based on the fact that the human body holds different sensitivities to vibrations at different frequencies,and applies this concept to the dynamic assessment on non-stationary vehicles.The study mainly includes two parts,the first is the input numerical calculation of the front and the rear wheels,and the second is the dynamical response analysis of suspension system subjected to non-stationary random excitations.Precise time integration method is used to obtain the vertical acceleration of suspension barycenter and the pitching angular acceleration,both root mean square(RMS)values of which are illustrated in different accelerating cases.The results show that RMS values of non-stationary random excitations are functions of time and increase as the speed increases at the same time.The DFD of vertical acceleration is finally analyzed using time-frequency analysis technique,and the conclusion is obviously that the DFD has a trend to the low frequency region,which would be significant reference for active suspension design under complex driving conditions.展开更多
文摘基于心里声学客观参量的GA-BP声品质预测模型能够准确的预测稳态排气噪声声品质。对于非稳态噪声研究,引入正则化非稳态回归技术(RNR)优化计算维格纳-威尔分布(WVD)的时频方法,建立新的声品质参量SQP-RW(Sound Quality Parameter Base on RNR-WVD),用此参量替换掉与满意度相关性较小的客观参量。同时,以Morlet小波基函数作为隐含层结点的传递函数构建小波神经网络(Wavelet Neural Network,WNN),并用GA优化小波神经网络层间的权值和阈值,构造出GA-WNN并用于非稳态排气噪声声品质预测。结果表明:GA-WNN在非稳态排气噪声声品质预测上比GA-BP神经网络更加准确;引入SQP-RW参量,模型具有更高的精度,更能体现出非稳态信号特征及声品质特点。
文摘车身板面贡献量分析作为研究车身振动对车内噪声影响的重要内容,常用声学传递向量(acoustic transfer vector,ATV)仿真计算来实现。为了进一步探究车身振动对车内语音清晰度的影响,通过对语音清晰度客观参量与主观评价分值的比较,确定以非稳态加速工况下的语言可懂度指数(speech intelligibility index,SII)为指标,运用ATV仿真手段找出对语音清晰度影响最大的面板。分析结果显示车身顶棚面板对语音清晰度影响最大。针对分析结果,采用遗传算法搜寻和ATV逆运算仿真相结合的方法,有针对性地进行了车身顶棚阻尼敷设并加以验证。结果表明,基于语音清晰度车身板面贡献情况的优化设计,有效地改善了非稳态全油门加速工况下的车内语音清晰程度,提高了车内声音品质。
基金This work was supported by the National Natural Science Foundation of China(No.51705205)。
文摘The dynamic responses of suspension system of a vehicle travelling at varying speeds are generally nonstationary random processes,and the non-stationary random analysis has become an important and complex problem in vehicle ride dynamics in the past few years.This paper proposes a new concept,called dynamic frequency domain(DFD),based on the fact that the human body holds different sensitivities to vibrations at different frequencies,and applies this concept to the dynamic assessment on non-stationary vehicles.The study mainly includes two parts,the first is the input numerical calculation of the front and the rear wheels,and the second is the dynamical response analysis of suspension system subjected to non-stationary random excitations.Precise time integration method is used to obtain the vertical acceleration of suspension barycenter and the pitching angular acceleration,both root mean square(RMS)values of which are illustrated in different accelerating cases.The results show that RMS values of non-stationary random excitations are functions of time and increase as the speed increases at the same time.The DFD of vertical acceleration is finally analyzed using time-frequency analysis technique,and the conclusion is obviously that the DFD has a trend to the low frequency region,which would be significant reference for active suspension design under complex driving conditions.
