基于小波熵的非稳态声品质评价参数研究

PDF(1500 KB)

振动与冲击 ›› 2016, Vol. 35 ›› Issue (14) : 83-89.

论文

基于小波熵的非稳态声品质评价参数研究

夏小均1，徐中明1,2，严涛1，赖诗洋1，贺岩松1,2

作者信息 +

The research on sound metric of unstable acoustic signal based on wavelet entropy

Xia Xiaojun1, Xu Zhongming1, 2, Yan Tao1, Lai Shiyang1, He Yansong1, 2

Author information +

文章历史 +

摘要

以非稳态声信号为对象，针对现有小波变换计算的小波熵在反映声信号时-频特征存在的不足，提出了改进的冗余小波分解算法并构造了零相位巴特沃斯小波滤波器。通过复合的时变和频变信号，验证了基于该方法计算的小波熵能更加准确的体现信号的时变和能量分布特性。提取了反映时频能量大致特性的小波熵均值作为非稳态声品质的客观评价参数,并应用于汽车关门声品质的分析评价中，计算了该声信号传统心理声学参数，完成了声样本的主观评价试验并获得到各声样本的偏好性评价绩效值。通过主客观相关性分析表明，小波熵均值与主观评价有更高的相关性，比传统的心理声学能好的描述和预测主观评价结果。

Abstract

Taking unsteady signal as object, the improved redundant wavelet algorithm is carried out and the zero-phase Butterworth wavelet filter is constructed in view of the deficiencies of existing wavelet transform when calculating the wavelet entropy. The characteristic of the wavelet entropy calculated by this method, which accurately reflecting the time-varying signal and energy distribution of a time and frequency varying signal, is verified. The wavelet entropy mean that roughly reflect the time-frequency energy features is extracted as an objective evaluation of the unstable sound quality parameters. And the wavelet entropy mean is applied to the quality analysis and evaluation of car door closing, traditional psychoacoustic parameters of each acoustic signal are calculated. Subjective evaluation test of these sound samples is completed and the preferential evaluation value of each sound samples is obtained. The correlation analysis with subjective preference evaluations and objective parameters shows that the sound metric defined by wavelet entropy mean has the higher correlation with the subjective evaluation, and can describe and forecast the subjective evaluation results more accurately.

导出引用

夏小均1，徐中明1,2，严涛1，赖诗洋1，贺岩松1,2. 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

Xia Xiaojun1, Xu Zhongming1, 2, Yan Tao1, Lai Shiyang1, He Yansong1, 2. The research on sound metric of unstable acoustic signal based on wavelet entropy[J]. Journal of Vibration and Shock, 2016, 35(14): 83-89

参考文献

[1] 申秀敏,左曙光,韩乐, 等. 基于支持向量机的车内噪声声品质预测[J]. 振动、测试与诊断, 2011, 31(1): 55-58，128.
Shen Xiumin, Zuo Shuguang,Han Le, et al. Interior Vehicle Noise Quality Prediction Using Support Vector Machines[J], Journal of Vibration Measurement & Diagnosis, 2011, 31(1): 55-58，128.
[2] Etienne Parizet,Erald Guyader,Valery Nosulenko. Analysis of car door closing sound quality [J]. Applied Acoustics 69 (2008) 12–22.
[3] 杨川, 于德介. 基于伪WIGNER-VILLE分布的汽车关门声品质评价参数研究[J]. 机械工程学报, 2011(24):91-96.
YANG Chuan,YU Dejie. Research on the sound metric of door slamming sound based on pseudo wigner-ville distribution [J]. Journal of Mechanical Engineering, 2011. 47(24):91-96.
[4] 王长山，张立军.汽车关门声声品质评价方法的研究[J].汽车工程,2011.33（10）: 902-906，901.
Wang Changshan,Zhang Lijun. A Study on the Method of Evaluating the Sound Quality of Vehicle Door Closing Noise [J]. Automotive Engineering, 2011.33（10）: 902-906，901.
[5] 徐中明,张芳,周小林,等.汽车喇叭声品质主观评价与分析[J]. 汽车工程, 2013, 35(2): 188-192.
Xu Zhongming, Zhang Fang, Zhou Xiaolin, et al. Subjective evaluation and analysis on car horn sound quality [J], Automotive Engineering, 2013, 35(2): 188-192.
[6] 徐中明,张瑜,刘建利,等.汽车雨刮系统噪声品质分析[J].汽车工程. 2014, (8): 1009-1013.
Xu Zhongming, Zhang yu, Liu jianli, et al. Sound Quality Analysis of Wiper System Noise in Cars [J]. Automotive Engineering, 2014, (8): 1009-1013.
[7] 徐中明,夏小均,贺岩松,等.汽车发动机启动声品质评价与分析[J]. 振动与冲击, 2014, 33(11): 142-147.
XU Zhong-ming, XIA Xiaojun, HE Yansong, et al. Analysis and evaluation of car engine starting sound quality [J]. Journal of Vibration and Shock, 2014, 33(11): 142-147.
[8] Scholl D, Yang B. Wavelet-based visualization, separation, and synthesis tools for sound quality of impulsive noises[R].SAE Technical Paper, 2003
[9] 张宁宁,王宏,付荣荣. 基于小波熵的驾驶疲劳脑电信号特征提取[J]. 汽车工程,2013, 35(12):1139-1142
Zhang Ningning, Wang Hong, Fu Rongrong.Feature Extraction of Fatigued Driver's Electroencephalogram Signals Based on Wavelet Entropy [J]. Automotive Engineering, 2013, 35(12):1139-1142
[10] 罗荣, 田福庆, 冯昌林, 等. 冗余小波包改进及其在齿轮箱故障诊断中应用[J]. 机械工程学报, 2014,50(15):82-88.
Luo Rong,Tian Fuqing,Zhoufei, et al .Improved redundant wavelet packet decomposition and its application in gearbox fault diagnosis[J], 2014, 50(15) :82-88.
[11] 孙增寿,范科举. 基于提升小波熵指标的梁板组合桥损伤识别研究[J], 振动与冲击,2012.31(12):114-117
SUN Zeng-shou,FAN Ke-ju.Damage detection for a grid-slab combined bridge based on lifting wavelet entropy indexes[J]. Journal of Vibration and Shock, 2012.31(12):114-117.
[12] Nha Nguyen,An Vo,Inchan Choi , et al. Stationary Wavelet Entropy-Based Clustering Approach Accurately Predicts Gene Expression[J].Journal of Computational Biology,2015.22(15):236-249.
[13] 程正兴．小波分析算法与应用[M]．西安：西安电子科技大学出版社．1998．
CHENG ZH X．Wavelet analysis algorithm and application [M]. Xi'an Electronic Science &Technology University Press，1998．
[14] 罗荣, 田福庆, 周菲, 等. 巴特沃斯小波构造及其在故障诊断中的应用[J]. 华中科技大学学报(自然科学版), 2013,41(10):68-73.
Luo Rong,Tian Fuqing,Zhoufei, et al.Construction of Butterworth wavelet and its application in fault diagnosis [J], Journal of Huazhong University of Science and Technology (Nature Science Edition), 2013,41(10):68-73.
[15] 傅勤毅, 章易程, 应力军, 等. 滚动轴承故障特征的小波提取方法[J]. 机械工程学报, 2001(02):30-32.
Fu Qinyi,Zhang Yicheng,Ying Lijun, et al.Extraction of failure character signal of rolling element bearings by wavelet[J]. Chinese Journal of Mechanical Engineering, 2013, 41(10):68-73.
[16] Chouard B,Hempel T.A semantic differential design especially developed for the evaluation of interior car sounds.ASA-EAA-DAGA Joint Meeting,Berlin,Germany,1999.
[17] 毛东兴, 俞悟周, 王佐民. 声品质成对比较主观评价的数据检验及判据[J]. 声学学报, 2005(05).
MAO Dongxing,YU Wuzhou,WANG Zuomin.Statistical validation and criterion for paired comparison data in sound quality evaluation[J].Acta Acustica,2005,30(5):468-472.