基于声发射的滚动轴承损伤定位方法研究

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Abstract The fault characteristic frequencies of low-speed rolling element bearing is low, and is greatly affected by the speed variation. It is difficult to identify the fault in those bearings by spectrum analysis. In this paper, a fault localization method for bearing damage based on the time difference of arrival (TDOA) of acoustic emission is proposed, which does not rely on the speed of acoustic emission signal. The optimal time difference can be obtained by minimize the variation of TDOA on each band of wavelet package decomposition. The pencil-lead break experiments on the ring of the bearing show that high localization accuracy can be achieved. The experiments carried out on the bearing test bench also demonstrates that the damage locations can be found with minor errors. This localization method does not depend on the rotating speed and frequency analysis, which has great advantage for the fault diagnosis and location of variable speed and large bearings.

Key words： Acoustic emission rolling element bearing fault localization time difference of arrival wavelet package decomposition

Received: 25 January 2019 Published: 28 July 2020

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	Articles by authors
	LIU Xiaoqin
	TANG Linjiang
	HOU Kaize
	WU Xing
	WANG Zhihai

Cite this article:

LIU Xiaoqin,TANG Linjiang,HOU Kaize, et al. Fault localization for rolling bearing based on AE[J]. JOURNAL OF VIBRATION AND SHOCK, 2020, 39(15): 176-182.

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http://jvs.sjtu.edu.cn/EN/ OR http://jvs.sjtu.edu.cn/EN/Y2020/V39/I15/176

[1]. 王楠, 孙凤久, 陈长征.基于小波分析的低速重载轴承故障诊断[J]. 东北大学学报（自然科学版）, 2005, 26(1): 77-79.
WANG Nan, SUN Feng-Jiu, ChEN Chang-Zheng. Fault diagnosis based on wavelet analysis for low-speed heavy-duty roller bearing[J]. Journal of Northeastern University, 2005, 26(1): 281-283.
[2]. 王宗炼, 任会兰, 宁建国. 基于小波变换降噪的声发射源定位方法[J]. 振动与冲击, 2018, 37 (4):226-232，248.
WANG Zonglian;REN Huilan;NING Jianguo. Acoustic emission source location based on wavelet transform de-noising[J]. Journal of Vibration and Shock, 2018, 37 (4):226-232,248.
[3]. Matthew R Pearson, Mark Eaton, Carol Featherston, Rhys Pullin and Karen Holford. Improved acoustic emission source location during fatigue and impact events in metallic and composite structures [J]. Structural Health Monitoring. 2017, 16(4): 382–399.
[4]. 郝如江,卢文秀,褚福磊.声发射检测技术用于滚动轴承故障诊断的研究综述[J].振动与冲击,2008,27(3):75-79.
Ru-Jiang H , Wen-Xiu LU , Fu-Lei C . REVIEW OF DIAGNOSIS OF ROLLING ELEMENT BEARINGS DEFAULTS BY MEANS OF ACOUSTIC EMISSION TECHNIQUE[J]. Journal of Vibration & Shock, 2008, 27(3):75-79.
[5]. Brandon Van Hecke, David He and Yongzhi Qu. On the Use of Spectral Averaging of Acoustic Emission Signals for Bearing Fault Diagnostics [J]. Journal of Vibration and Acoustics.2014,136(10):061009-1-13.
[6]. 张晓涛,唐力伟,王平等.轴承故障声发射信号多频带共振解调方法[J].振动、测试与诊断,2015,35(2):363-368.
Zhang Xiaotao,Tang Liwei,Wang Ping. Multi-band resonance demodulation method for bearing fault acoustic emission signal[J]. Journal of Vibration，Measurement&Diagnosis，2015,35(2):363-368.
[7]. Farzad Hemmati, Mohammed Alqaradawi and Mohamed S Gadala. Rolling element bearing fault diagnostics using acoustic emission technique and advanced signal processing [J]. Journal of Engineering Tribology. 2016, 230(1):64–77.
[8]. Arash Amini, Mani Entezami, Mayorkinos Papaelias. Onboard detection of railway axle bearing defects using envelope analysis of high frequency acoustic emission signals [J]. Case Studies in Nondestructive Testing and Evaluation.2016,6(A): 8-16.
[9]. Cheng-Wei Fei , Yat-Sze Choy, Guang-Chen Bai and Wen-Zhong Tang. Multi-feature entropy distance approach with vibration and acoustic emission signals for process feature recognition of rolling element bearing faults [J]. Structural Health Monitoring.2018,17(2):156-168.
[10]. Faris Elasha , Matthew Greaves and David Mba. Planetary bearing defect detection in a commercial helicopter main gearbox with vibration and acoustic emission [J]. Structural Health Monitoring.2018,17(5): 1192 - 1212.
[11]. 陈国华,梁峻,王新华.基于线性时差的回转支承声发射源定位及修正[J].华南理工大学学报(自然科学版),2013,41(4):142-146.
Chen Guo-hua,Liang Jun,Wang Xin-hua. TDOA-Based Location and Its Correction of Acoustic Emission Source with Slewing Ring[J]. Journal of South China University of Technology(Natural Science Edition), 2013, 41(4):142-146.
[12]. 赵江海, 杨慧, 顾菊平等. 基于短时能量的声发射源定位方法研究[J]. 振动与冲击, 2013, (23):110-114.
ZHAO Jiang-hai;YANG Hui;GU Ju-ping;YE Xiao-dong. Acoustic emission source locating method based on short-time energy[J]. Journal of Vibration and Shock, 2013, (23):110-114.
[13]. Bing Q. Li, Bruno Gonçalves da Silva, Herbert Einstein. Laboratory hydraulic fracturing of granite: Acoustic emission observations and interpretation [J],Engineering Fracture Mechanics. 2019, 209:200-220.
[14]. 张宇, 卢文秀, 褚福磊. 基于声发射衰减特性的故障行星轮定位研究[J]. 振动与冲击, 2017, 36 (3):14-19.
ZHANG Yu;LU Wenxiu;CHU Fulei. Faulted planet gear positioning based on attenuation characteristics of AE signals[J]. Journal of Vibration and Shock, 2017, 36 (3):14-19.
[15]. 丁雷,曾锐利,沈虹等.基于香农熵特征的发动机故障诊断方法[J].振动与冲击, 2018,37(21):233-239.
DING Lei, ZENG Ruili, SHEN Hong, ZHAO Huimin. ZENG Rong. An engine fault diagnosis method based on Shannon entropy features [J]. Journal of Vibration and Shock, 2018,37(21):233-239.
[16]. Davide Bianchi, Erwin Mayrhofer, Martin Gröschl, Gerhard Betz, András Vernes. Wavelet packet transform for detection of single events in acoustic emission signals[J], Mechanical Systems and Signal Processing.2015,64-65: 441-451.