The Diagnosis Approach for Rolling Bearing Fault based on Kurtosis Criterion EMD and Hilbert Envelope Spectrum

被引:0
|
作者
Luo, Cheng [1 ]
Jia, MinPing [1 ]
Wen, Yue [1 ]
机构
[1] Southeast Univ, Sch Mech Engn, Nanjing, Jiangsu, Peoples R China
基金
中国国家自然科学基金;
关键词
EMD; Kurtosis criterion; Hibert envelope spectrum; roller bearings; fault diagnosis; EMPIRICAL MODE DECOMPOSITION;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
A fault diagnosis approach based on empirical mode decomposition(EMD), Hilbert envelope spectrum and Kurtosis criterion is proposed, by considering the nonlinear and non-stationary characteristic of fault signal for rolling bearing. The fault signals are decomposed into a sum of intrinsic mode functions(IMFs) with EMD decomposing process. Also, some of the IMFs are selected to reconstruct the signal through using Kurtosis criterion, which can be used to represent the fault information. And then, the determination of specific fault for rolling bearings are achieved by comparing the envelope spectrum of the reconstructed signal with the fault characteristic frequency. It can be found from the result that the proposed approach can be well used in the fault information extraction for the rolling bearing, and with a good application prospect.
引用
收藏
页码:692 / 696
页数:5
相关论文
共 50 条
  • [21] Bearing Fault Detection Using Envelope Spectrum Based on EMD and TKEO
    Hui, Li
    Zheng, Haiqi
    [J]. FIFTH INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS AND KNOWLEDGE DISCOVERY, VOL 3, PROCEEDINGS, 2008, : 142 - +
  • [22] A Fault Diagnosis Method based on Singular Spectrum Decomposition and Envelope Autocorrelation for Rolling Bearing
    Niu, Ben
    Li, Maolin
    Jia, Linshan
    Shan, Lei
    Liang, Lin
    [J]. PROCEEDINGS OF 2019 IEEE 8TH JOINT INTERNATIONAL INFORMATION TECHNOLOGY AND ARTIFICIAL INTELLIGENCE CONFERENCE (ITAIC 2019), 2019, : 920 - 925
  • [23] Rolling Bearing Fault Diagnosis Using Sample Entropy and 1.5 Dimension Spectrum Based on EMD
    Zhong, Xianyou
    Zhao, Chunhua
    Dong, Haijiang
    Liu, Xianming
    Zeng, Liangcai
    [J]. ADVANCES IN MECHATRONICS AND CONTROL ENGINEERING, PTS 1-3, 2013, 278-280 : 1027 - +
  • [24] Frequency band selection based on the kurtosis of the squared envelope spectrum and its application in bearing fault diagnosis
    Hu, Chongqing
    Peng, Zhongxiao
    [J]. PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART C-JOURNAL OF MECHANICAL ENGINEERING SCIENCE, 2016, 230 (7-8) : 1113 - 1125
  • [25] Spectral kurtosis of multiwavelet for fault diagnosis of rolling bearing
    Wang, Xiaodong
    He, Zhengjia
    Zi, Yanyang
    [J]. Hsi-An Chiao Tung Ta Hsueh/Journal of Xi'an Jiaotong University, 2010, 44 (03): : 77 - 81
  • [26] A fault diagnosis approach for roller bearing based on IMF envelope spectrum and SVM
    Yang, Yu
    Yu, Dejie
    Cheng, Junsheng
    [J]. MEASUREMENT, 2007, 40 (9-10) : 943 - 950
  • [27] An Intelligent Fault Diagnosis Of Rolling Bearing Based On EMD And Correlation Analysis
    Li Jianbao
    Peng Tao
    [J]. PROCEEDINGS OF THE 29TH CHINESE CONTROL CONFERENCE, 2010, : 3931 - 3936
  • [28] Feature Extraction Based on Hierarchical Improved Envelope Spectrum Entropy for Rolling Bearing Fault Diagnosis
    Chen, Zhixiang
    Yang, Yang
    He, Changbo
    Liu, Yongbin
    Liu, Xianzeng
    Cao, Zheng
    [J]. IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2023, 72
  • [29] An Improved EMD Method for Fault Diagnosis of Rolling Bearing
    Li, Yongbo
    Xu, Minqiang
    Huang, Wenhu
    Zuo, Ming J.
    Liu, Libin
    [J]. 2016 PROGNOSTICS AND SYSTEM HEALTH MANAGEMENT CONFERENCE (PHM-CHENGDU), 2016,
  • [30] Bearing Fault Diagnosis Method Based on Hilbert Envelope Demodulation Analysis
    Wang, Nan
    Liu, Xia
    [J]. 2018 3RD INTERNATIONAL CONFERENCE ON ADVANCED MATERIALS RESEARCH AND MANUFACTURING TECHNOLOGIES (AMRMT 2018), 2018, 436