Fault Diagnosis of Induction Motor based on Multi-sensor Data Fusion

被引:0
|
作者
Li Shu-ying [1 ]
Tian Mu-qin [1 ]
Xue Lei [2 ]
机构
[1] Taiyuan Univ Technol, Shanxi Prov Key Lab Coal Mine Equipment & Safety, Taiyuan 030024, Peoples R China
[2] Econ & Tech Inst Shanxi Elect Power Co, Taiyuan 030001, Peoples R China
来源
MATERIAL SCIENCE, CIVIL ENGINEERING AND ARCHITECTURE SCIENCE, MECHANICAL ENGINEERING AND MANUFACTURING TECHNOLOGY II | 2014年 / 651-653卷
关键词
multi-sensor data fusion; fault diagnosis; D-S evidential theory;
D O I
10.4028/www.scientific.net/AMM.651-653.729
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
For the conclusions of single parameter fault feature diagnosis has some uncertainty, in induction motor early fault, we proposed the use of multi-sensor data fusion technology, acted signal processing to the collected current, vibration and temperature, extracted feature information failure, fused the evidence independent with each other using D-S evidence fusion rules. According to the final combination results of all the evidence, combined with intermediate results of the evidence combination, we achieved the accurate identification of induction motor rotor early failures and composite fault. The diagnosis examples show that the use of multi-sensor data fusion technology can significantly improve the accuracy and reliability of early fault diagnosis.
引用
收藏
页码:729 / +
页数:2
相关论文
共 50 条
  • [41] Gearbox fault diagnosis based on RGT-MFFIN and multi-sensor fusion image generation
    Xie, Guangpeng
    Zhan, Hongfei
    Yu, Junhe
    Wang, Rui
    Cheng, Youkang
    ENGINEERING RESEARCH EXPRESS, 2024, 6 (03):
  • [42] Evidence combination based on prospect theory for multi-sensor data fusion
    Xiao, Fuyuan
    ISA TRANSACTIONS, 2020, 106 : 253 - 261
  • [43] Aeroengine Bearing Fault Diagnosis Based on Convolutional Neural Network for Multi-sensor Information Fusion
    Yang J.
    Wan A.
    Wang J.
    Shan T.
    Miao X.
    Li K.
    Zuo Q.
    Zhongguo Dianji Gongcheng Xuebao/Proceedings of the Chinese Society of Electrical Engineering, 2022, 42 (13): : 4933 - 4941
  • [44] Gearbox Fault Diagnosis Based on Multi-Sensor and Multi-Channel Decision-Level Fusion Based on SDP
    Fu, Yuan
    Chen, Xiang
    Liu, Yu
    Son, Chan
    Yang, Yan
    APPLIED SCIENCES-BASEL, 2022, 12 (15):
  • [45] APPLICATION OF MULTI-SENSOR INFORMATION FUSION TECHNOLOGY IN THE POWER TRANSFORMER FAULT DIAGNOSIS
    Li, Yong-Wei
    Li, Wei
    Han, Xing-De
    Li, Jing
    PROCEEDINGS OF 2009 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-6, 2009, : 29 - 33
  • [46] Rotating machinery fault diagnosis method based on multi-level fusion framework of multi-sensor information
    Xiao, Xiangqu
    Li, Chaoshun
    He, Hongxiang
    Huang, Jie
    Yu, Tian
    INFORMATION FUSION, 2025, 113
  • [47] Non-contact diagnosis for gearbox based on the fusion of multi-sensor heterogeneous data
    Sun, Dingyi
    Li, Yongbo
    Jia, Sixiang
    Feng, Ke
    Liu, Zheng
    INFORMATION FUSION, 2023, 94 : 112 - 125
  • [48] Fault diagnosis of axial piston pumps with multi-sensor data and convolutional neural network
    Qun Chao
    Haohan Gao
    Jianfeng Tao
    Chengliang Liu
    Yuanhang Wang
    Jian Zhou
    Frontiers of Mechanical Engineering, 2022, 17
  • [49] Fault diagnosis of axial piston pumps with multi-sensor data and convolutional neural network
    Chao, Qun
    Gao, Haohan
    Tao, Jianfeng
    Liu, Chengliang
    Wang, Yuanhang
    Zhou, Jian
    FRONTIERS OF MECHANICAL ENGINEERING, 2022, 17 (03)
  • [50] Fault diagnosis of axial piston pumps with multi-sensor data and convolutional neural network
    Qun CHAO
    Haohan GAO
    Jianfeng TAO
    Chengliang LIU
    Yuanhang WANG
    Jian ZHOU
    Frontiers of Mechanical Engineering, 2022, 17 (03) : 243 - 257