Research on Fault Tendency Prediction of Complex Equipment Based on Multi-Source Information Fusion

被引:0
|
作者
Hu, Wenhua [1 ]
Guo, Ming-Ming [1 ]
Shi, Lin [1 ]
机构
[1] Mech Engn Coll, Dept Opt & Elect Engn, Shijiazhuang, Peoples R China
关键词
fault predication; multi-Information fusion; evidence theory; condition monitoring;
D O I
暂无
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Aiming at the problem that there is much information and it's difficult to predict the fault trend for modern complex equipment, the equipment fault trend prediction model which is based on multi-source information fusion is put forward. Based on the analysis of mutual relationship of fusion information source and fusion strategy, the arithmetic of different information fusion and the method of fault trend prediction are researched. An example of the radar transmitter is given and analyzed. The method makes full use of the differences and complementary in performance of the various information sources and makes up for the defect of the single information. It can improve the reliability and precision of fault prediction, which can make the predicted result more scientific and accurate.
引用
收藏
页码:661 / 664
页数:4
相关论文
共 50 条
  • [31] Fault diagnosis method of hydraulic system based on multi-source information fusion and fractal dimension
    Wang, Wei
    Li, Yan
    Song, Yuling
    [J]. JOURNAL OF THE BRAZILIAN SOCIETY OF MECHANICAL SCIENCES AND ENGINEERING, 2021, 43 (12)
  • [32] Design of improved fault-tolerant filtering algorithm based on multi-source information fusion
    Cong, Ning
    Wang, Wei
    Zhu, Zuo-qing
    [J]. 2020 CHINESE AUTOMATION CONGRESS (CAC 2020), 2020, : 918 - 923
  • [33] Fault diagnosis method of hydraulic system based on multi-source information fusion and fractal dimension
    Wei Wang
    Yan Li
    Yuling Song
    [J]. Journal of the Brazilian Society of Mechanical Sciences and Engineering, 2021, 43
  • [34] Single-Ended Fault Location Method Based on Multi-Source Transient Information Fusion
    Deng, Feng
    Xu, Fan
    Zeng, Zhe
    Zhang, Zhen
    Feng, Sixu
    [J]. Diangong Jishu Xuebao/Transactions of China Electrotechnical Society, 2022, 37 (13): : 3201 - 3212
  • [35] The DMF: Fault Diagnosis of Diaphragm Pumps Based on Deep Learning and Multi-Source Information Fusion
    Meng, Fanguang
    Shi, Zhiguo
    Song, Yongxing
    [J]. PROCESSES, 2024, 12 (03)
  • [36] Rotor unbalance fault diagnosis using DBN based on multi-source heterogeneous information fusion
    Yan, Jihong
    Hu, Yuanyuan
    Guo, Chaozhong
    [J]. 2ND INTERNATIONAL CONFERENCE ON SUSTAINABLE MATERIALS PROCESSING AND MANUFACTURING (SMPM 2019), 2019, 35 : 1184 - 1189
  • [37] New Method of Fault Location for Active Distribution Network Based on Multi-source Information Fusion
    Li, Zhenzhao
    Wang, Zengping
    Zhang, Yuxi
    [J]. Dianwang Jishu/Power System Technology, 2023, 47 (08): : 3448 - 3456
  • [38] Fault Risk Early Warning Method of Distribution Network Based on Multi-source Information Fusion
    Yang, Fan
    Liu, Jun
    Wan, Junjie
    [J]. 2022 9TH INTERNATIONAL FORUM ON ELECTRICAL ENGINEERING AND AUTOMATION, IFEEA, 2022, : 311 - 314
  • [39] Application of a Bayesian Network Based on Multi-Source Information Fusion in the Fault Diagnosis of a Radar Receiver
    Liu, Boya
    Bi, Xiaowen
    Gu, Lijuan
    Wei, Jie
    Liu, Baozhong
    [J]. SENSORS, 2022, 22 (17)
  • [40] Research on Human Gait Phase Recognition Algorithm Based on Multi-Source Information Fusion
    Wang, Yu
    Song, Quanjun
    Ma, Tingting
    Yao, Ningguang
    Liu, Rongkai
    Wang, Buyun
    [J]. ELECTRONICS, 2023, 12 (01)