Application of fuzzy pattern recognition in intelligent fault diagnosis systems

被引:1
|
作者
He, HY [1 ]
Wang, DP [1 ]
Ma, SP [1 ]
机构
[1] Tsing Hua Univ, Sch Publ Policy & Management, Beijing 100084, Peoples R China
关键词
fuzzy math; membership degree; pattern recognition; fault diagnosis;
D O I
10.1117/12.441647
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In this paper, we attempt to argue that the uncertainty coming from fuzzy information is ubiquitous in an intelligent fault diagnosis system and that fuzzy pattern recognition is an appropriate tool for the diagnosis of faults in complex devices. In the first place, the characteristics of the faults in a complex equipment system are introduced along with the fuzzy pattern recognition method and principle in intelligent fault diagnosis systems. Then, on the base of the above discussion, the paper gives an applied approach to fault diagnosis that combines the valve value rule with the maximum membership degree rule. Lastly, the practicability and validity of the method is illustrated through a practical example.
引用
收藏
页码:262 / 267
页数:6
相关论文
共 50 条
  • [41] Fuzzy artmap neural network and its application to fault diagnosis of navigation systems
    Zhang, HY
    Chan, CW
    Cheung, KC
    Ye, YJ
    AUTOMATICA, 2001, 37 (07) : 1065 - 1070
  • [42] Fuzzy-neuro technique-based intelligent fault diagnosis in electrical motor systems
    Gao, XZ
    Ovaska, SJ
    COMPUTER APPLICATIONS IN INDUSTRY AND ENGINEERING, 2000, : 292 - 297
  • [43] APPLICATION OF FUZZY PATTERN RECOGNITION ON FINGERPRINT PROCESSING
    Li Yuan
    ICICTA: 2009 SECOND INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTATION TECHNOLOGY AND AUTOMATION, VOL II, PROCEEDINGS, 2009, : 660 - 663
  • [44] Application of fuzzy pattern recognition in lithology determination
    Xu, Shaohua
    Ma, Zhenxiang
    Li, Zifang
    Daqing Shiyou Xueyuan Xuebao/Journal of Daqing Petroleum Institute, 1995, 19 (03): : 43 - 46
  • [45] Fault Diagnosis of Construction Elevator Based on Fuzzy Recognition
    Liu, Limei
    Li, Jianbin
    OPTICAL, ELECTRONIC MATERIALS AND APPLICATIONS II, 2012, 529 : 459 - +
  • [46] Fault diagnosis in an induction motor by pattern recognition methods
    Casimir, R
    Boutleux, E
    Clerc, G
    IEEE INTERNATIONAL SYMPOSIUM ON DIAGNOSTICS FOR ELECTRIC MACHINES, POWER ELECTRONICS AND DRIVES, PROCEEDINGS, 2003, : 294 - 299
  • [47] Simulation-Based Benefit Analysis of Pattern Recognition Application in Intelligent Transportation Systems
    Ibrahim, Hamdy
    Far, Behrouz H.
    2015 IEEE 28TH CANADIAN CONFERENCE ON ELECTRICAL AND COMPUTER ENGINEERING (CCECE), 2015, : 507 - 512
  • [48] Clonal fuzzy intelligent system for fault diagnosis of cracked beam
    Parhi, Dayal R.
    Sahu, Sasmita
    INTERNATIONAL JOURNAL OF DAMAGE MECHANICS, 2018, 27 (06) : 840 - 858
  • [49] The application of fuzzy logic in radar fault diagnosis
    Zhang, X.
    Han, J.
    Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics, 2001, 23 (02): : 90 - 93
  • [50] PEM fuel cell fault diagnosis via a hybrid methodology based on fuzzy and pattern recognition techniques
    Escobet, Antoni
    Nebot, Angela
    Mugica, Francisco
    ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2014, 36 : 40 - 53