Spectral entropy: a complementary index for rolling element bearing performance degradation assessment

被引:120
|
作者
Pan, Y. N. [1 ]
Chen, J. [1 ]
Li, X. L. [2 ]
机构
[1] Shanghai Jiao Tong Univ, State Key Lab Mech Syst & Vibrat, Shanghai 200240, Peoples R China
[2] Hangzhou Bearing Test & Res Ctr, State Testing Lab, Hangzhou, Zhejiang, Peoples R China
关键词
spectral entropy; performance degradation assessment; bearing accelerated life test; FAULT-DIAGNOSIS; STATISTICAL MOMENTS; MACHINE; VIBRATION; ALGORITHM; ENVELOPE; DEFECTS;
D O I
10.1243/09544062JMES1224
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
Performance degradation assessment has been proposed to realize equipment's near-zero downtime and maximum productivity. Exploring effective indices is crucial for it. In this study, rolling element bearing has been taken as a research object, spectral entropy is proposed to be as a complementary index for its performance degradation assessment, and its accelerated life test has been performed to collect vibration data over a whole lifetime (normal-fault-failure). Results of both simulation and experiment show that spectral entropy is an effective complementary index.
引用
收藏
页码:1223 / 1231
页数:9
相关论文
共 50 条
  • [41] The weak fault diagnosis and condition monitoring of rolling element bearing using minimum entropy deconvolution and envelop spectrum
    Jiang, Ruilong
    Chen, Jin
    Dong, Guangming
    Liu, Tao
    Xiao, Wenbin
    PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART C-JOURNAL OF MECHANICAL ENGINEERING SCIENCE, 2013, 227 (C5) : 1116 - 1129
  • [42] Intelligent Diagnosis of Rolling Element Bearing Based on Refined Composite Multiscale Reverse Dispersion Entropy and Random Forest
    Liu, Aiqiang
    Yang, Zuye
    Li, Hongkun
    Wang, Chaoge
    Liu, Xuejun
    SENSORS, 2022, 22 (05)
  • [43] Fault diagnosis of rolling element bearing based on symmetric cross entropy of neutrosophic sets
    Kumar, Anil
    Gandhi, C. P.
    Zhou, Yuqing
    Tang, Hesheng
    Xiang, Jiawei
    MEASUREMENT, 2020, 152
  • [44] Intelligent fault diagnosis of rolling element bearing using hierarchical multiscale dispersion entropy
    Yan X.
    Jia M.
    Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering, 2021, 37 (11): : 67 - 75
  • [45] Continuous Health Monitoring of Rolling Element Bearing Based on Nonlinear Oscillatory Sample Entropy
    Noman, Khandaker
    Li, Yongbo
    Wang, Shun
    IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2022, 71
  • [46] Refined composite multiscale fuzzy entropy: Localized defect detection of rolling element bearing
    Li, Yongjian
    Miao, Bingrong
    Zhang, Weihua
    Chen, Peng
    Liu, Jihua
    Jiang, Xiaoliang
    JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY, 2019, 33 (01) : 109 - 120
  • [47] An unsupervised and enhanced deep belief network for bearing performance degradation assessment
    Xu, Fan
    Fang, Zhou
    Tang, Ruoli
    Li, Xin
    Tsui, Kwok Leung
    MEASUREMENT, 2020, 162 (162)
  • [48] Performance Prediction of Rolling Element Bearing with Utilization of Support Vector Regression
    Chauhan, Shivani
    Yadav, Pradip
    Tiwari, Prashant
    Upadhyay, S. H.
    Mishra, Niraj
    RELIABILITY, SAFETY AND HAZARD ASSESSMENT FOR RISK-BASED TECHNOLOGIES, 2020, : 535 - 543
  • [49] Rolling bearing performance degradation assessment based on deep belief network and improved support vector data description
    Pan, Yuna
    Cheng, Daolai
    Wei, Tingting
    Jia, Yuchen
    MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2022, 181
  • [50] Assessment of bearing performance degradation via extension and EEMD combined approach
    Liu Yu-mei
    Zhao Cong-cong
    Xiong Ming-ye
    Zhao Ying-hui
    Qiao Ning-guo
    Tian Guang-dong
    JOURNAL OF CENTRAL SOUTH UNIVERSITY, 2017, 24 (05) : 1155 - 1163