基于时频感知加权的车辆路面冲击声品质评价

朱洪林; 宋帅; 吴昱东; 杨明亮; 税永波; 丁渭平

doi:10.3969/j.issn.0258-2724.20211060

基于时频感知加权的车辆路面冲击声品质评价

doi: 10.3969/j.issn.0258-2724.20211060

1.
西南交通大学机械工程学院，四川成都 610031
2.
重庆工商职业学院智能制造与汽车学院，重庆 401520

基金项目: 重庆市自然科学基金（cstc2021jcyj-msxmX1020) ；四川省科技计划项目2020YFG0130

详细信息

作者简介:
朱洪林（1989—），男，博士研究生，研究方向为车辆声振舒适性、车辆智能化理论与技术，E-mail：zhlswjtu@foxmail.com

通讯作者:
丁渭平（1968—），男，教授，研究方向为车辆声振舒适性、车辆智能化理论与技术，E-mail：dwp@swjtu.edu.cn

中图分类号: U467.11
计量
- 文章访问数: 389
- HTML全文浏览量: 158
- PDF下载量: 46
- 被引次数: 0
出版历程
- 收稿日期: 2021-12-24
- 修回日期: 2022-04-06
- 网络出版日期: 2023-01-03
- 刊出日期: 2022-04-11

Evaluation of Vehicle Road Impact Sound Quality Based on Time-Frequency Perception Weighting

1.
School of Mechanical Engineering , Southwest Jiaotong University, Chengdu 610031, China
2.
School of Intelligent Manufacturing and Automotive , Chongqing Technology & Business Institute, Chongqing 401520, China

摘要

摘要:
为表征与量化人对路面冲击声的主观感受，首先，对减速带工况冲击非平稳噪声信号进行声时感知时长定义，同时根据人耳听声可辨性将声时历程分为冲击段、峰值段及衰减段；进而，以小波变换提取冲击噪声中的主冲击与多重微冲击特征信息，组成冲击声品质评价的基础特征阵；然后，类比峰值因子法定义频域滤波因子，并基于序关系分析法确定时变感知加权系数，组建时频滤波网络对基础特征阵加权且建立冲击声品质时频感知评价指标；最后，基于实车过减速带冲击噪声测试数据计算声品质指标，并进行对比验证. 研究结果表明：所提时频感知加权评价指标与主观评价的相关系数在车速20 km/h时为0.927，在车速30 km/h时为0.922；在考虑路面冲击声声时历程全程评价时，经典的声品质评价指标（特征频带时变响度）与主观评价的相关系数在车速20 km/h时为0.933，在车速30 km/h时为0.649；所提时频感知加权评价方法对于车速为20 km/h与30 km/h的情况具有较好的适用性.
- 路面冲击 /
- 声品质 /
- 声时感知时长 /
- 小波变换 /
- 时频感知加权
Abstract:
In order to characterize and quantify a person’s subjective perception of road impact sound, firstly, the acoustic time perception duration of the impact non-stationary noise signal of the speed bump condition was defined, and the acoustic time history was divided into the impact section, the peak section and the attenuation section according to the discernibility of the human ear. The main impact and multiple micro-impact feature information of the impact noise were extracted by the wavelet transforms, and the feature information was used to form the basic feature matrix for impact sound quality evaluation. Then, the frequency domain filter factor was defined by referring to the crest factor method, and the time-varying perceptual weighting coefficient was determined based on the sequence relation analysis method, and the time-frequency filter network was established to weight the basic feature matrix and establish the impact sound quality evaluation index. Finally, based on the test data of the impact noise of the actual vehicle driving through the speed bump, the sound quality index was calculated, and comparative verification was carried out. The results show that the correlation coefficient between the proposed time-frequency perception weighted evaluation index and subjective evaluation is 0.927 at 20 km/h and 0.922 at 30 km/h. When considering the road impact acoustic time history evaluation, the correlation coefficient between the classic sound quality evaluation index(characteristic frequency band time-varying loudness) and subjective evaluation is 0.933 at 20 km/h and 0.649 at 30 km/h. The proposed time-frequency perception weighted evaluation method has good applicability for the conditions of 20 km/h and 30 km/h.
- road impact /
- quality control /
- perception time during sound /
- wavelet transforms /
- time-frequency perception weighting

HTML全文

图 1 路面冲击声品质评价指标提取流程

Figure 1. Process of road impact sound quality evaluation method

下载: 全尺寸图片幻灯片

图 2 减速带与声压测点

Figure 2. Speed bump and sound pressure measuring location

下载: 全尺寸图片幻灯片

图 3 减振器阻尼因素水平示例

Figure 3. Example of damping factor levels

下载: 全尺寸图片幻灯片

图 4 S_TF相关性分析

Figure 4. Correlation analysis of S_TF

下载: 全尺寸图片幻灯片

图 5 路面冲击感知时长界定与数据对比

Figure 5. Definition of road impact perception time and data comparison

下载: 全尺寸图片幻灯片

图 6 S_TF特征阵分布对比

Figure 6. Characteristic matrix distribution of S_TF

下载: 全尺寸图片幻灯片

图 7 时变响度模型相关性分析

Figure 7. Correlation analysis of time-varying loudness method

下载: 全尺寸图片幻灯片

表 1 路面冲击声品质主观评价等级评分定义

Table 1. Definition of subjective evaluation grade of road impact sound quality

评价等级	没有不舒适	略微不舒适	不舒适	明显不舒适	极不舒适
评分	1～2	3～4	5	6～8	9～10

下载: 导出CSV

表 2 路面冲击声品质指标

Table 2. Road impact sound quality indicators

试验编号	车速/ （km·h⁻¹）	T_V/ms	T_S/ms	T_M/ms	T_D/ms	S_TF/	主观评分
T_est1	20	500	100	160	240	6.81	3.87
T_est2	20	500	100	160	240	4.66	3.62
T_est3	20	500	100	160	240	6.75	4.37
T_est4	20	500	100	160	240	24.17	5.50
T_est5	20	500	100	160	240	39.19	5.62
T_est6	20	500	100	160	240	18.61	5.37
$ \vdots $	$\vdots $	$\vdots $	$\vdots $	$\vdots $	$\vdots $	$\vdots $	$\vdots $
T_est27	30	340	80	100	160	45.54	5.75
T_est28	30	340	80	100	160	42.31	5.75
T_est29	30	340	80	100	160	41.46	5.62
T_est30	30	340	80	100	160	39.41	5.37

下载: 导出CSV

表 3 S_TF相关分析统计

Table 3. The correlation analysis statistics of S_TF

指标	编号	车速/（km·h⁻¹）	相关系数	置信水平
S_TF	5	20	0.927	0.99
S_TF	5	30	0.922	0.99

下载: 导出CSV

表 4 时变响度模型主要区别

Table 4. Main difference of the time-varying loudness model

类别	尺度/级数	传递特性	频域掩蔽	时域掩蔽
Zwicker 时变响度	Bark [0～24]	外耳与中耳综合考虑	图表法	单一时间常量
Moore 时变响度	ERB [1.8～38.9]	外耳与中耳独立考虑	机理数学模型	多时间常量

下载: 导出CSV

表 5 时变响度模型相关分析统计

Table 5. Correlation analysis statistics of time-varying loudness method

指标	编号	车速/（km·h⁻¹）	相关系数	置信水平
N_maxZwicker	1	20	0.732	0.99
N_maxZwicker	1	30	0.587	0.95
N_Zwicker	2	20	0.933	0.99
N_Zwicker	2	30	0.583	0.95
N_maxMoore	3	20	0.866	0.99
N_maxMoore	3	30	0.649	0.95
N_Moore	4	20	0.926	0.99
N_Moore	4	30	0.168

下载: 导出CSV

参考文献(17)

[1]	徐中明,周小林,张芳,等. Moore响度在车内噪声分析中的应用[J]. 振动与冲击,2013,32(1): 169-173. doi: 10.3969/j.issn.1000-3835.2013.01.035 XU Zhongming, ZHOU Xiaolin, ZHANG Fang, et al. Application of Moore loudness in a vehicle interior noise analysis[J]. Journal of Vibration and Shock, 2013, 32(1): 169-173. doi: 10.3969/j.issn.1000-3835.2013.01.035
[2]	韩雪,朴胜春,付金山. 舰船辐射噪声听觉节奏的时变响度特征提取[J]. 哈尔滨工程大学学报,2020,41(4): 487-492. doi: 10.11990/jheu.201904011 HAN Xue, PIAO Shengchun, FU Jinshan. Time-varying loudness feature extraction of the audition rhythm of ship radiation noise[J]. Journal of Harbin Engineering University, 2020, 41(4): 487-492. doi: 10.11990/jheu.201904011
[3]	The British Standards Institution. Acoustics-methods for calculating loudness part 1 Zwicker method: BS ISO 532-1[S]. [S.l.]: BSI Standards Limited, 2017.
[4]	周明刚,董琦飞,刘阳,等. Zwicker时变响度的一种计算方法[J]. 中国机械工程,2014,25(22): 3073-3076. doi: 10.3969/j.issn.1004-132X.2014.22.017 ZHOU Minggang, DONG Qifei, LIU Yang, et al. A calculation method of zwicker time-varying loudness[J]. China Mechanical Engineering, 2014, 25(22): 3073-3076. doi: 10.3969/j.issn.1004-132X.2014.22.017
[5]	MOORE B C J, GLASBERG B R, VARATHANATHAN A, et al. A loudness model for time-varying sounds incorporating binaural inhibition[J]. Trends in Hearing, 2016, 20: 2331216516682698.1-2331216516682698.16.
[6]	MOORE B C J, JERVIS M, HARRIES L, et al. Testing and refining a loudness model for time-varying sounds incorporating binaural inhibition[J]. The Journal of the Acoustical Society of America, 2018, 143(3): 1504-1513. doi: 10.1121/1.5027246
[7]	The British Standards Institution. Acoustics-methods for calculating loudness part 2 moore-glasberg method: BS ISO 532-2[S]. [S.l.]: BSI Standards Limited, 2017
[8]	张觉慧,张立军,于佳. 汽车时变噪声的响度计算模型适用性分析[J]. 同济大学学报(自然科学版),2010,38(9): 1345-1349. doi: 10.3969/j.issn.0253-374x.2010.09.017 ZHANG Juehui, ZHANG Lijun, YU Jia. Applicability of different loudness models to time-varying sound of vehicle[J]. Journal of Tongji University (Natural Science), 2010, 38(9): 1345-1349. doi: 10.3969/j.issn.0253-374x.2010.09.017
[9]	刘红星,吴九汇,张俊,等. 基于时频域分形维数差的声品质评价新方法[J]. 噪声与振动控制,2018,38(增2): 526-531. LIU Hongxing, WU Jiuhui, ZHANG Jun, et al. A new sound quality evaluation approach based on time-frequency domain fractal dimension difference[J]. Noise and Vibration Control, 2018, 38(S2): 526-531.
[10]	KIM H W, LEE S K, NA E W. Sound quality evaluation of the impact noise induced by road courses having an impact bar and speed bumps in a passenger car[J]. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, 2010, 224(6): 735-747. doi: 10.1243/09544070JAUTO1296
[11]	夏小均,徐中明,严涛,等. 基于小波熵的非稳态声品质评价参数研究[J]. 振动与冲击,2016,35(14): 83-89. doi: 10.13465/j.cnki.jvs.2016.14.013 XIA Xiaojun, XU Zhongming, YAN Tao, et al. Sound metric of unsteady acoustic signal based on wavelet entropy[J]. Journal of Vibration and Shock, 2016, 35(14): 83-89. doi: 10.13465/j.cnki.jvs.2016.14.013
[12]	LIANG L Y, CHEN S M, LI P R. The evaluation of vehicle interior impact noise inducing by speed bumps based on multi-features combination and support vector machine[J]. Applied Acoustics, 2020, 163: 107212.1-107212.21.
[13]	黄海波,黄晓蓉,苏瑞强,等. 基于EEMD与GA-小波神经网络的传动系声品质预测[J]. 振动与冲击,2017,36(9): 130-137. doi: 10.13465/j.cnki.jvs.2017.09.020 HUANG Haibo, HUANG Xiaorong, SU Ruiqiang, et al. Sound metric prediction of a power train system based on EEMD and GA-wavelet neural network[J]. Journal of Vibration and Shock, 2017, 36(9): 130-137. doi: 10.13465/j.cnki.jvs.2017.09.020
[14]	边姜,段向雷,李贝. 基于Hilbert变换的车辆过坎振动衰减评价方法[J]. 汽车工程学报,2019,9(5): 327-331. BIAN Jiang, DUAN Xianglei, LI Bei. Evaluation of vehicle vibration attenuation when passing over speed bumps based on Hilbert transform[J]. Chinese Journal of Automotive Engineering, 2019, 9(5): 327-331.
[15]	蒋淑霞,罗意平. 基于小波阈值去噪与二次经验模态分解的发动机点火波形分析方法[J]. 汽车工程,2015,37(4): 380-386. doi: 10.3969/j.issn.1000-680X.2015.04.002 JIANG Shuxia, LUO Yiping. An analysis method for engine ignition waveform based on wavelet threshold denoising and secondary empirical mode decomposition[J]. Automotive Engineering, 2015, 37(4): 380-386. doi: 10.3969/j.issn.1000-680X.2015.04.002
[16]	张迅,赵宇,阮灵辉,等. 基于小波变换分析箱梁振动噪声的时频特性[J]. 西南交通大学学报,2020,55(1): 109-117. doi: 10.3969/j.issn.0258-2724.20170768 ZHANG Xun, ZHAO Yu, RUAN Linghui, et al. Time-frequency characteristics of box-girder vibration and noise based on wavelet transform[J]. Journal of Southwest Jiaotong University, 2020, 55(1): 109-117. doi: 10.3969/j.issn.0258-2724.20170768
[17]	康诺华. 实用非参数统计[M]. 3版. 北京: 人民邮电出版社, 2006: 381-382.