Research on running condition recognition of mechanical equipment and fault diagnosis method based on fuzzy evaluation

被引：0
|
作者：
Chai, Baoming [1 ]
Gao, Weijin [1 ]
Gao, Xuepan [1 ]
机构：
[1] Hebei Univ Engn, Handan 056038, Hebei, Peoples R China
来源：
ADVANCES IN SUPERALLOYS, PTS 1 AND 2 | 2011年 / 146-147卷
关键词：
Measurement Space; Fault Diagnosis; Classification Weight;
D O I：
10.4028/www.scientific.net/AMR.146-147.530
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
Apply fuzzy evaluation method to research on running state recognition of mechanical equipment and fault diagnosis, define concept of classification weight of index, give out calculation method. On the basis of analysis of fault datasheet that records expert knowledge, build mathematical model of recognition and evaluation on running condition of mechanical equipment based on uncertainty measurement. Calculation examples show the effectiveness of this method and the reliability of calculation results.
引用
收藏
页码：530 / 535
页数：6
相关论文
共 50 条
  • [1] Intelligent fault diagnosis method of mechanical equipment based on fuzzy pattern recognition
    Huo, Jiaofei
    Lin, Dong
    Qi, Wanqiang
    JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2020, 38 (04) : 3657 - 3664
  • [2] Research on Mechanical Equipment Fault Diagnosis Method Based on Deep Learning and Information Fusion
    Jiang, Dongnian
    Wang, Zhixuan
    SENSORS, 2023, 23 (15)
  • [3] Research on the Application of Fuzzy Fault Tree Analysis Method in the Machinery Equipment Fault Diagnosis
    Chen, Yuliang
    Zhang, Tiejun
    2010 2ND INTERNATIONAL ASIA CONFERENCE ON INFORMATICS IN CONTROL, AUTOMATION AND ROBOTICS (CAR 2010), VOL 1, 2010, : 84 - 87
  • [4] Fuzzy Condition Pattern Recognition and Fault Diagnosis for Spacecraft
    荣吉利
    黄文虎
    纪常伟
    Journal of Harbin Institute of Technology, 1997, (03) : 103 - 105
  • [5] Fault Diagnosis Method Research of Mechanical Equipment Based on Sensor Correlation Analysis and Deep Learning
    Bai, Tangbo
    Yang, Jianwei
    Duan, Lixiang
    Wang, Yanxue
    SHOCK AND VIBRATION, 2020, 2020
  • [6] SVDD-based research on the fault diagnosis of mechanical equipment system
    Jiang, ZQ
    Li, LJ
    Zhang, L
    Shi, JF
    ISTM/2005: 6th International Symposium on Test and Measurement, Vols 1-9, Conference Proceedings, 2005, : 1994 - 1997
  • [7] Research on Remote Fault Diagnosis of Mechanical Equipment Based on Cloud Computing
    Gang Jianhua
    AGRO FOOD INDUSTRY HI-TECH, 2017, 28 (03): : 3197 - 3201
  • [8] Fault Diagnosis Method of Mechanical Equipment Based on Convolutional Neural Network
    Zhou, Jun
    Zhang, Wenfeng
    Sun, WeiZhao
    PROCEEDINGS OF THE 2019 INTERNATIONAL CONFERENCE ON ROBOTICS, INTELLIGENT CONTROL AND ARTIFICIAL INTELLIGENCE (RICAI 2019), 2019, : 459 - 465
  • [9] Research on condition monitoring and fault diagnosis of Metallurgical machinery and equipment
    Zhengrong-guan
    Junping-li
    Xinwu-wang
    ADVANCES IN MECHANICAL ENGINEERING, PTS 1-3, 2011, 52-54 : 504 - 510
  • [10] RESEARCH ON MEDICAL EQUIPMENT CONDITION MONITORING AND MECHANISM OF FAULT DIAGNOSIS
    Zheng, L.
    Shi, Z. Q.
    Luo, Y. G.
    Kang, J.
    BASIC & CLINICAL PHARMACOLOGY & TOXICOLOGY, 2016, 119 : 47 - 47
12345