A Compound Fault Integrated Diagnosis Method for Rotating Machinery Base on Dimensionless Immune Detector

被引:0
|
作者
Sun, Guoxi [1 ]
Qin, Aisong [1 ,2 ]
Zhang, Qinghua [1 ]
Hu, Qin [1 ,3 ]
Si, Xiaosheng [4 ]
机构
[1] Guangdong Univ Petrochem Technol, Coll Comp & Elect Informat, Maoming 525000, Peoples R China
[2] Taiyuan Univ Technol, Coll Informat Engn, Taiyuan 030024, Peoples R China
[3] Guangdong Univ Technol, Sch Automat, Guangzhou 510006, Peoples R China
[4] Tsinghua Univ, Dept Automat, Beijing 100084, Peoples R China
基金
中国国家自然科学基金;
关键词
Compound fault diagnosis; Dimensionless parameter; Evidence reasoning; Rotating machinery; EVIDENTIAL REASONING ALGORITHM; DECISION-ANALYSIS;
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
Real-time and accuracy fault diagnosis is the key technique to realize timely effective maintenance and health management for rotating machinery, most faults of which are compound under actual working conditions. Many compound faults are coupled with each other, fuzzy, object and some complex characteristics so it is a bottleneck problem which is very tough to break through in fault diagnosis field. Early research results indicate that diagnosis with dimensionless parameters have got good effects in single fault for rotating machinery, but under simulating actual working state of compound faults, there are obvious overlap in ranges of dimensionless parameters calculated by vibration monitoring data of each compound faults, that is to say, it is hard to distinguish the ranges of dimensionless parameters of each fault, causing complexity of diagnosis rise, and the existing method is hard to deal with this problem. To solve the difficult problem, an online fusion fault diagnosis method for rotating machinery based on dimensionless immune detector and evidence reasoning (ER) is proposed. Experimental result demonstrates that the method can realize effectively real-time fault diagnose for rotating machinery and has high potential applications in real project.
引用
收藏
页码:4390 / 4394
页数:5
相关论文
共 50 条
  • [1] A DIMENSIONLESS IMMUNE INTELLIGENT FAULT DIAGNOSIS SYSTEM FOR ROTATING MACHINERY
    Shao, Longqiu
    Zhang, Qinghua
    Lei, Gaowei
    Su, Naiquan
    Yuan, Penghui
    [J]. TRANSACTIONS OF FAMENA, 2022, 46 (02) : 23 - 36
  • [2] Application of an Information Fusion Method to Compound Fault Diagnosis of Rotating Machinery
    Hu, Qin
    Qin, Aisong
    Zhang, Qinghua
    Sun, Guoxi
    Shao, Longqiu
    [J]. 2015 27TH CHINESE CONTROL AND DECISION CONFERENCE (CCDC), 2015, : 3859 - 3864
  • [3] Compound-Fault Diagnosis of Rotating Machinery: A Fused Imbalance Learning Method
    Zhang, Jingfei
    Zhang, Qinghua
    He, Xiao
    Sun, Guoxi
    Zhou, Donghua
    [J]. IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, 2021, 29 (04) : 1462 - 1474
  • [4] A rotating machinery fault diagnosis method based on multi-scale dimensionless indicators and random forests
    Hu, Qin
    Si, Xiao-Sheng
    Zhang, Qing-Hua
    Qin, Ai-Song
    [J]. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2020, 139
  • [5] A new fault diagnosis method of rotating machinery
    Chen, Chih-Hao
    Shyu, Rong-Juin
    Ma, Chih-Kao
    [J]. SHOCK AND VIBRATION, 2008, 15 (06) : 585 - 598
  • [6] A Novel Method for Fault Diagnosis of Rotating Machinery
    Tang, Meng
    Liao, Yaxuan
    Luo, Fan
    Li, Xiangshun
    [J]. ENTROPY, 2022, 24 (05)
  • [7] A method for intelligent fault diagnosis of rotating machinery
    Chen, CZ
    Mo, CT
    [J]. DIGITAL SIGNAL PROCESSING, 2004, 14 (03) : 203 - 217
  • [8] A Fault Diagnosis of Rotating Machinery Based on a Mutual Dimensionless Index and a Convolution Neural Network
    Su, Naiquan
    Zhang, Qinghua
    Zhou, Lingmeng
    Chang, Xiaoxiao
    Xu, Ting
    [J]. IEEE INTELLIGENT SYSTEMS, 2023, 38 (04) : 33 - 41
  • [9] Artificial Immune System Used in Rotating Machinery Fault Diagnosis
    Zhao, Linhui
    Zhou, Lihua
    Dai, Yaping
    Dai, Zhongjian
    [J]. PROCEEDINGS OF THE 2015 CHINESE INTELLIGENT AUTOMATION CONFERENCE: INTELLIGENT AUTOMATION, 2015, 337 : 65 - 74
  • [10] An efficient method for imbalanced fault diagnosis of rotating machinery
    Yang, Jingli
    Yin, Shuangyan
    Gao, Tianyu
    [J]. MEASUREMENT SCIENCE AND TECHNOLOGY, 2021, 32 (11)