Condition Monitoring of Broken Rotor Bars Using a Hybrid FMM-GA Model

被引：0
|
作者：
Seera, Manjeevan [1 ]
Lim, Chee Peng [2 ]
Loo, Chu Kiong [1 ]
机构：
[1] Univ Malaya, Fac Comp Sci & Informat Technol, Kuala Lumpur, Malaysia
[2] Deakin Univ, Ctr Intelligent Syst Res, Geelong, Vic, Australia
来源：
NEURAL INFORMATION PROCESSING, ICONIP 2014, PT III | 2014年 / 8836卷
关键词：
Condition monitoring; fault diagnosis; fuzzy min-max neural network; genetic algorithms; induction motor; INDUCTION-MOTORS; NEURAL-NETWORKS; CLASSIFICATION; MAINTENANCE; FAULTS;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A condition monitoring system for induction motors using a hybrid Fuzzy Min-Max (FMM) neural network and Genetic Algorithm (GA) is presented in this paper. Two types of experiments, one from the finite element method and another from real laboratory tests of broken rotor bars in an induction motor are conducted. The induction motor with broken rotor bars is operated under different load conditions. FMM is first used for learning and distinguishing between a healthy motor and one with broken rotor bars. The GA is then utilized for extracting fuzzy if-then rules using the don't care approach in minimizing the number of rules. The results clearly demonstrate the effectiveness of the hybrid FMM-GA model in condition monitoring of broken rotor bars in induction motors.
引用
收藏
页码：381 / 389
页数：9
相关论文
共 50 条
  • [1] Robust condition monitoring for early detection of broken rotor bars in induction motors
    Garcia-Escudero, Luis A.
    Duque-Perez, Oscar
    Morinigo-Sotelo, Daniel
    Perez-Alonso, Marcelo
    EXPERT SYSTEMS WITH APPLICATIONS, 2011, 38 (03) : 2653 - 2660
  • [2] Complete Ensemble Empirical Mode Decomposition on FPGA for Condition Monitoring of Broken Bars in Induction Motors
    Valtierra-Rodriguez, Martin
    Pablo Amezquita-Sanchez, Juan
    Garcia-Perez, Arturo
    Camarena-Martinez, David
    MATHEMATICS, 2019, 7 (09)
  • [3] Locating rotor broken bars in induction motors using finite element method
    Faiz, Jawad
    Ebrahimi, B. M.
    ENERGY CONVERSION AND MANAGEMENT, 2009, 50 (01) : 125 - 131
  • [4] Induction motors broken rotor bars detection using RPVM and neural network
    Bensaoucha, Saddam
    Bessedik, Sid Ahmed
    Ameur, Aissa
    Teta, Ali
    COMPEL-THE INTERNATIONAL JOURNAL FOR COMPUTATION AND MATHEMATICS IN ELECTRICAL AND ELECTRONIC ENGINEERING, 2019, 38 (02) : 596 - 615
  • [5] Application of Hybrid Wavelet-SVM Algorithm to Detect Broken Rotor Bars in Induction Motors
    Ghasemi, Shermineh
    Sadeghian, Alireza
    PROCEEDINGS OF 2021 IEEE 30TH INTERNATIONAL SYMPOSIUM ON INDUSTRIAL ELECTRONICS (ISIE), 2021,
  • [6] Broken Rotor Bars Detection in Induction Motors Running at Very Low Slip Using a Hall Effect Sensor
    Dias, Cleber Gustavo
    Pereira, Fabio Henrique
    IEEE SENSORS JOURNAL, 2018, 18 (11) : 4602 - 4613
  • [7] Condition Monitoring of Induction Motor for Broken Rotor Bar using Discrete Wavelet Transform & K-nearest Neighbor
    Patel, Viraj U.
    PROCEEDINGS OF THE 2019 3RD INTERNATIONAL CONFERENCE ON COMPUTING METHODOLOGIES AND COMMUNICATION (ICCMC 2019), 2019, : 520 - 524
  • [8] A hybrid detection method of broken rotor bars in cage induction motors
    Sun, LL
    Li, LH
    Xu, BQ
    2004 International Conference on Power System Technology - POWERCON, Vols 1 and 2, 2004, : 177 - 181
  • [9] Simple detection of broken rotor bars using field-oriented control
    Drobnic, K.
    Nemec, M.
    Fiser, R.
    Ambrozic, V.
    2012 15TH INTERNATIONAL POWER ELECTRONICS AND MOTION CONTROL CONFERENCE (EPE/PEMC), 2012,
  • [10] Multi-sensory Fault Diagnosis of Broken Rotor Bars Using Transfer Learning
    Aydin, Ilhan
    Akin, Erhan
    INTELLIGENT AND FUZZY SYSTEMS, INFUS 2024 CONFERENCE, VOL 1, 2024, 1088 : 349 - 356
12345