Cyclic statistics based neural network for early fault diagnosis of rolling element bearings

被引：0
|
作者：
Zhou, FC [1 ]
Chen, J [1 ]
He, J [1 ]
Bi, G [1 ]
Zhang, GC [1 ]
Li, FC [1 ]
机构：
[1] Shanghai Jiao Tong Univ, State Key Lab Vibrat Shock & Noise, Shanghai 200030, Peoples R China
来源：
ADVANCES IN NEURAL NETWORKS - ISNN 2004, PT 2 | 2004年 / 3174卷
关键词：
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：
This paper proposes a novel cyclic statistics based artificial neural network for early fault diagnosis of rolling element bearing, via which the real time domain signals obtained from a test rig are preprocessed by cyclic statistics to perform monitoring fault diagnosis. Three kinds of familiar faults are intentionally introduced in order to investigate typical rolling element bearing faults. The testing results are presented and discussed with examples of real time data collected from the test rig.
引用
收藏
页码：595 / 600
页数：6
相关论文
共 50 条
  • [1] Physics-Based Convolutional Neural Network for Fault Diagnosis of Rolling Element Bearings
    Sadoughi, Mohammadkazem
    Hu, Chao
    [J]. IEEE SENSORS JOURNAL, 2019, 19 (11) : 4181 - 4192
  • [2] Fault diagnosis based on dependent feature vector and probability neural network for rolling element bearings
    Chen, Xiaoyue
    Zhou, Jianzhong
    Xiao, Jian
    Zhang, Xinxin
    Xiao, Han
    Zhu, Wenlong
    Fu, Wenlong
    [J]. APPLIED MATHEMATICS AND COMPUTATION, 2014, 247 : 835 - 847
  • [3] Fault diagnosis of rolling bearings with recurrent neural network based autoencoders
    Liu, Han
    Zhou, Jianzhong
    Zheng, Yang
    Jiang, Wei
    Zhang, Yuncheng
    [J]. ISA TRANSACTIONS, 2018, 77 : 167 - 178
  • [4] A Neural-Symbolic Network for Interpretable Fault Diagnosis of Rolling Element Bearings Based on Temporal Logic
    Tian, Ruoyao
    Cui, Mengqian
    Chen, Gang
    [J]. IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2024, 73 : 1 - 14
  • [5] A fault diagnosis method for rolling element bearings based on ICEEMDAN and Bayesian network
    Liu, Zengkai
    Lv, Kanglei
    Zheng, Chao
    Cai, Baoping
    Lei, Gang
    Liu, Yonghong
    [J]. JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY, 2022, 36 (05) : 2201 - 2212
  • [6] A fault diagnosis method for rolling element bearings based on ICEEMDAN and Bayesian network
    Zengkai Liu
    Kanglei Lv
    Chao Zheng
    Baoping Cai
    Gang Lei
    Yonghong Liu
    [J]. Journal of Mechanical Science and Technology, 2022, 36 : 2201 - 2212
  • [7] Fault diagnosis of rolling element bearing based on artificial neural network
    Gunerkar, Rohit S.
    Jalan, Arun Kumar
    Belgamwar, Sachin U.
    [J]. JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY, 2019, 33 (02) : 505 - 511
  • [8] Fault diagnosis of rolling element bearing based on artificial neural network
    Rohit S. Gunerkar
    Arun Kumar Jalan
    Sachin U Belgamwar
    [J]. Journal of Mechanical Science and Technology, 2019, 33 : 505 - 511
  • [9] A Simple SOM Neural Network Based Fault Detection Model for Fault Diagnosis of Rolling Bearings
    Li, Zhichun
    [J]. ADVANCED DESIGN AND MANUFACTURING TECHNOLOGY III, PTS 1-4, 2013, 397-400 : 1321 - 1325
  • [10] Fault diagnosis of rolling element bearings using artificial neural networks
    Rajamani, L
    Dattagupta, R
    [J]. CRITICAL LINK: DIAGNOSIS TO PROGNOSIS, 1997, : 783 - 789
12345