Improved Fault Diagnosis of Rolling Bearing by Fast Kurtogram and Order Analysis

被引：0
|
作者：
Zhang X. [1 ,2 ]
Zhang C. [1 ]
Fan H. [1 ,2 ]
Mao Q. [1 ,2 ]
Yang Y. [1 ]
机构：
[1] School of Mechanical Engineering, Xi'an University of Science and Technology, Xi'an
[2] Shaanxi Key Laboratory of Mine Electromechanical Equipment Intelligent Monitoring, Xi'an
来源：
Zhendong Ceshi Yu Zhenduan/Journal of Vibration, Measurement and Diagnosis | 2021年 / 41卷 / 06期
关键词：
Fast kurtogram; Fault diagnosis; Order analysis; Rolling bearing; Variable rotating speed;
D O I：
10.16450/j.cnki.issn.1004-6801.2021.06.007
中图分类号：
学科分类号：
摘要：
For the variable speed condition, the vibration signal of the gearbox is characterized by non-stationary, strong interference and signal modulation, which make the rolling bearing fault difficult to be accurately diagnosed. Therefore, a fault envelope order spectrum analysis method with fast kurtogram for rolling bearings is proposed. The fast kurtogram is used to adaptively determine the filtering parameters, meanwhile, the time domain signal is bandpass filtered and enveloped to improve the signal-to-noise ratio. Furthermore, the time domain non-stationary signal after the envelope is resampled and converted into an angular pseudo-stationary signal to eliminate the "frequency ambiguity". Finally, the spectral analysis of envelope signal in the angular domain is used to obtain the order envelope spectrum, and the fault diagnosis of rolling bearing is realized by comparing with order features. The simulation and signal analysis experiments of the outer ring fault of the gearbox rolling bearing during the speed increases from 600~1 500 r/min are completed. The experiment results show that the proposed method has a maximum fault error order of 1.84%, which can effectively extract the fault characteristics of rolling bearings under variable speed conditions and judge the fault types of them. © 2021, Editorial Department of JVMD. All right reserved.
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页码：1090 / 1095
页数：5
相关论文
共 14 条
  • [1] ZHANG Xining, LEI Wei, LI Bing, Bearing fault detection and diagnosis method based on principal component analysis and hidden markov model, Journal of Xi'an Jiaotong University, 51, 6, pp. 1-7, (2017)
  • [2] CHEN Xianglong, FENG Fuzhou, ZHANG Bingzhi, Et al., Rolling bearing fault diagnosis with optimal resonant frequency band demodulation based on squared envelope spectral correlated kurtosis, Journal of Mechanical Engineering, 54, 21, pp. 90-100, (2018)
  • [3] SUN Wei, LI Xinmin, JIN Xiaoqiang, Et al., Feature extraction method based on EMD and envelope cepstrum, Journal of Vibration, Measurement & Diagnosis, 38, 5, pp. 1057-1062, (2018)
  • [4] XIONG Q, XU Y H, PENG Y Q, Et al., Low-speed rolling bearing fault diagnosis based on EMD denoising and parameter estimate with alpha stable distribution, Journal of Mechanical Science & Technology, 31, 4, pp. 1587-1601, (2017)
  • [5] ZHU Xiaoyan, WANG Yongjie, ZHANG Yuqi, Et al., Method of incipient fault diagnosis of bearing based on adaptive optimal morlet wavelet, Journal of Vibration, Measurement & Diagnosis, 38, 5, pp. 1021-1029, (2018)
  • [6] LIN Tong, CHEN Guo, TENG Chunyu, Et al., Rolling bearing collaborative fault diagnosis technology for casing vibration signal, Journal of Aerospace Power, 33, 10, pp. 2376-2384, (2018)
  • [7] LUAN Xiaochi, SHA Yundong, Technology to extract weak fault characteristic signal of intermediate bearing of some turbofan engine, Science Technology and Engineering, 18, 13, pp. 167-174, (2018)
  • [8] SU Wensheng, WANG Fengtao, ZHANG Zhixin, Et al., Application of EMD denoising and spectral kurtosis in early fault diagnosis of rolling element bearings, Journal of Vibration and Shock, 29, 3, pp. 18-21, (2010)
  • [9] DING Kang, HUANG Zhizhong, LIN Huibin, A weak fault diagnosis method for rolling element bearings based on Morlet wavelet and spectral kurtosis, Journal of Vibration Engineering, 27, 1, pp. 128-135, (2014)
  • [10] HAO Gaoyan, LIU Yongqiang, LIAO Yingying, A rolling bearing fault diagnosis algorithm based on improved order envelope spectrum, Journal of Vibration and Shock, 35, 15, pp. 144-148, (2016)
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