Single-channel  Vibration  Signal Separation by Combining  Wavelet Decomposition with Time-frequency Analysis

Abstract

Abstract:

Single-channel mechanical vibration signal-separation is an ill-conditioned problem,and in traditional methods, the blind source separation of vibration signals often ignores the nonstationarity.For this reason,a method on single-channel vibration signal separation was proposed based on wavelet decomposition and TFA.The method firstly used wavelet decomposition and reconstruction to make the single-channel signals into multi-channel signals,solving the problem of underdetermined blind source separation;Secondly,based on time-frequency analysis BSS was used to effectively analyze the non-stationary signals, then the estimation source signals were obtained,achieving blind source separation of non-stationary signals.Simulation and experimental results vertify the effectiveness of this method, and show the method can solve the problem of BSS of nonstationary single-channel vibration signals.

Key words: blind source separation(BSS);wavelet , decomposition;time-frequency analysis(TFA);fault diagnosis

摘要：

针对单通道振动信号盲源分离是一个病态问题，且传统的振动信号盲源分离方法往往忽略信号的非平稳性的问题,提出了一种融合小波分解与时频分析的单通道振动信号盲源分离方法。首先利用小波分解与重构将单通道信号转化为多通道信号，解决了盲源分离的欠定问题;然后利用基于时频分析的盲源分离算法分析非平稳信号，得到源信号的估计信号,实现了非平稳信号盲源分离。仿真和实验结果表明，该方法可以有效地解决单通道非平稳振动信号的盲源分离问题。

关键词: 盲源分离, 小波分解, 时频分析, 故障诊断

CLC Number:

TN911.7

Meng Zong, Wang Xiaoyan, Ma Zhao. Single-channel Vibration Signal Separation by Combining Wavelet Decomposition with Time-frequency Analysis[J]. China Mechanical Engineering, 2015, 26(20): 2751-2756.

孟宗, 王晓燕, 马钊. 融合小波分解与时频分析的单通道振动信号盲分离方法[J]. 中国机械工程, 2015, 26(20): 2751-2756.

References

[1]Jutten C,Herault J.lind Separation of Source Part I:an Adaptive Algorithm Based on Neuromimetic Architecture[J].Signal Processing,1991,24:1-10.
[2]申永军,张光明,杨绍普,等.基于Gabor变换的欠定盲信号分离新方法[J].振动、测试与诊断,2011,31(3):309-313.
Shen Yongjun,Zhang Guangming,Yang Shaopu,et al.New Method for Blind Source Separation in Under-determined Mixtures Based on Gabor Transform[J].Journal of Vibration, Measurement & Diagnosis,2011,31(3):309-313.
[3]毋文峰,陈小虎,苏勋家.基于经验模式分解的单通道机械信号盲分离[J].机械工程学报,2011,47 (4)：12-16.
Wu Wenfeng,Chen Xiaohu,Su Xunjia.Blind Source Separation of Single-channel Mechanical Signal Based on Empirical Mode Decomposition[J].Journal of Mechanical Engineering,2011,47(4):12-16.
[4]李志农,刘卫兵,易小兵.基于局域均值分解的机械故障欠定盲源分离新方法[J].机械工程学报,2011,47(7):97-102.
Li Zhinong,Liu Weibing,Yi Xiaobing.Underdetermined Blind Source Separation Method of Machine Faults Based on Local Mean Decomposition[J].Journal of Mechanical Engineering,2011,47(7):97-102.
[5]李晓晖,傅攀.基于EEMD的单通道盲源分离在轴承故障诊断中的应用[J].中国机械工程,2014,25(7):924-930.
Li Xiaohui,Fu Pan.Application of Signal-channel Blind Source Separation Based on EEMD in Bearing Fault Diagnosis[J].China Mechanical Engineering,2014,25(7):924-930.
[6]陈建国,王奉涛,朱泓,等.改进ICA与HHT在转子故障诊断上的应用[J].中国机械工程,2009,20(17):2059-2062.
Chen Jianguo,Wang Fengtao,Zhu Hong,et al.Application of Improved ICA & HHT in Fault Diagnosis of Rotors[J].China Mechanical Engineering,2009,20(17):2059-2062.
[7]李强,付聪,江虹,等.融合经验模态分解与时频分析的单通道振动信号分离研究[J].振动与冲击,2013,32(5):122-126.
Li Qiang,Fu Cong,Jiang Hong,et al.Single-channel Vibration Signal Separation by Combining Empirical Mode Decomposition with Time-frequency Analysis[J].Journal of Vibration and Shock,2013,32(5):122-126.
[8]吴强,孔凡让,何清波,等.基于小波变换和ICA的滚动轴承早期故障诊断[J].中国机械工程,2012,23(7):835-840.
Wu Qiang,Kong Fanrang,He Qingbo,et al.Early Fault Diagnosis of Rolling Element Bearings Based on Wavelet Transform and Independent Component Analysis[J].China Mechanical Engineering,2012,23(7):835-840.
[9]张俊红,李林洁,马文朋,等.EMD-ICA联合降噪在滚动轴承故障诊断中的应用[J].中国机械工程,2013,24(11):1468-1472.
Zhang Junhong,Li Linjie,Ma Wenpeng,et al.Application of EMD-ICA to Fault Diagnosis of Rolling Bearings[J].China Mechanical Engineering,2013,24(11):1468-1472.
[10]向玲,唐贵基,胡爱军.旋转机械非平稳振动信号的时频分析比较[J].振动与冲击,2010,29(2):42-45.
Xiang Ling,Tang Guiji,Hu Aijun.Vibration Signal’S Time-frequency Analysis and Comparison for a Rotating Machinery[J]. Journal of Vibration and Shock,2010,29(2):42-45.
[11]绍忍平,曹精明,李永龙.基于EMD小波阈值去噪和时频分析的齿轮故障模式识别与诊断[J].振动与冲击,2012, 31(8):96-101.
Shao Renping,Cao Jingming,Li Yonglong.Gear Fault Pattern Identification and Diagnosis Using Time-frequency Analysis and Wavelet Threshold Denoising Based on EMD[J].Journal of Vibration and Shock,2012,31(8):96-101.

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Single-channel Vibration Signal Separation by Combining Wavelet Decomposition with Time-frequency Analysis

融合小波分解与时频分析的单通道振动信号盲分离方法

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