A de-noising research for fault acoustic emission signal based on EMD and correlation coefficient

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Journal of Vibration and Shock ›› 2017, Vol. 36 ›› Issue (19) : 71-77.

Liu Dongying1 Deng Aidong1 Liu Zhenyuan2Li Jing3Zhang Rui1Huang Hongwei4

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Abstract

A number of non-stationary and non-linear noises often interfere with the useful acoustic emission(AE)signals in the world,which induce the difficulty in AE recognition.Based on the principle of correlation coefficient,a de-noising method for rubbing AE signals of the rotating machine based on empirical mode decomposition(EMD) was proposed.The original noise polluted AE signal can be divided into several intrinsic mode functions(IMFs) derived from EMD.Through calculating each correlation coefficient between IMFs and AE siginal and finding out their changing regularities with the EMD’s characteristic of filtering,the modes reflecting the important structures of the signal were chosen to combine to form partially reconstruct de-noised signal.Simulations were conducted for rub-impact AE signal polluted by different kinds of noises using this method.Experimental results indicate that this method can not only effectively and adaptively remove noises,but also get the stable results which can not be affected by subjective parameters.

Key words

:rub-impact / acoustic emission / signal de-noising / EMD / correlation coefficient

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Liu Dongying1 Deng Aidong1 Liu Zhenyuan2Li Jing3Zhang Rui1Huang Hongwei4. A de-noising research for fault acoustic emission signal based on EMD and correlation coefficient[J]. Journal of Vibration and Shock, 2017, 36(19): 71-77

References

[1]孟传民,邓艾东,蒋章,等.转子碰摩故障的声发射与振动特征分析[J].汽轮机技术,2010,52(6):443-446.
MENG Chuan-min,DENG Ai-dong,JIANGZhang,etal.Experimental analysis of characteristic of AE and vibration in rotor rub-impact fault[J].TurbineTechnology,2010,52(6):443-446.
[2]MbaD.Applicability of acoustic emissions to monitoring the mechanical integrity of bolted structures in low speed rotating machinery:case study[J].NDT&E International,2002,35(5):293-300.
[3]Donoho D L.De-noising by soft-thresholding [J].IEEE Transactions onInformation Theory,1995,41(3):613-627.
[4]陈果.基于小波分析的转子故障信号自适应降噪技术研究[J].航空动力学报,2008,23(1): 9-16.
CHEN Guo. Research on self-adaptive de-noising technique for rotor faults signal based on wavelet analysis[J].Journal of Aerospace Power, 2008,23(1): 9-16.
[5]Huang N E, Shin Z, Long S R,et al. The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis[J] .Proc R Soc Lord A,1998,454 (1971):903-995.
[6]Huang B, KunothA. An optimization based empirical mode decomposition scheme[J]. Journal of Computational and Applied Mathematics,2013,240(1):174-183.
[7]谭善文,秦树人,汤宝平.Hilbert-Huang变换的滤波特性及其应用[J].重庆大学学报,2004, 27 (2): 9-12.
TAN Shan-wen,QIN Shu-ren,TANFBao-ping.Thefiltering character of Hilbert-Huang transform and its application[J].Journal of Chongqing University,2004, 27 (2): 9-12.
[8]陈隽,李想.运用总体经验模式分解的疲劳信号降噪方法[J].振动、测试与诊断,2011, 31(1): 15-19.
CHEN Jun,LIXiang.Application of ensemble empirical mode decomposition to noise reduction of fatigue signal[J].Journal of Vibration,Mearsurement&Diagnosis, 2011, 31(1): 15-19.
[9]Boudraa A O, Cexus J C.EMD-Based Signal Filtering[J]. IEEE Transactions on Instrumentation and Measurement,2007,56(6):2196-2202.
[10]孙伟峰,彭玉华,许建华.基于EMD的激光超声信号去噪方法[J].山东大学学报(工学版),2008, 38(5) :1-6.
SUN Wei-feng,PENG Yu-hua,XU Jian-hua.A de-noising method for laser ultrasonic signal based on EMD[J].Journal ofShanDong University(EngineeringScience), 2008, 38(5) :1-6.
[11]王婷.EMD算法及其在信号去噪中的应用[D]. 哈尔滨工程大学, 2010.
[12]程军圣,于德介,杨宇.EMD方法在转子局部碰摩故障诊断中的应用[J].振动、测试与诊断,2006,26(1):24-27.
CHENG Jun-sheng,YU De-jie,YANGYu.Application of EMD to local rub-impact fault diagnosis in rotor systems[J]. Journal of Vibration,Mearsurement&Diagnosis,2006,26(1):24-27.
[13]邓艾东. 基于声发射的旋转机械碰摩故障诊断基础问题研究[D]. 东南大学, 2008.
[14] Zheng G T,McFadden P D. A time-frequency distribution for analysis of signals with transient components and its application to vibration analysis[J].Journal of vibration andacoustics-transactionsofthe ASME, July 1999,121(3):328-333.
[15]Donoho D L. Ideal spatial adaptation via wavelet shrinkage.Biometrika, 1994,81(3): 425-455.