Numerical magnetic field analysis and signal processing for fault diagnostics of electrical machines

被引：25
|
作者：
Pöyhönen, S
Negrea, M
Jover, P
Arkkio, A
Hyötyniemi, H
机构：
[1] Aalto Univ, Control Engn Lab, Dept Automat & Syst Technol, FIN-02150 Espoo, Finland
[2] Aalto Univ, Lab Electromech, Dept Elect Engn, FIN-02150 Espoo, Finland
来源：
COMPEL-THE INTERNATIONAL JOURNAL FOR COMPUTATION AND MATHEMATICS IN ELECTRICAL AND ELECTRONIC ENGINEERING | 2003年 / 22卷 / 04期
关键词：
condition monitoring; electromagnetic fields; electrical machines; finite element method; signal processing; fault analysis;
D O I：
10.1108/03321640310482931
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
Numerical magnetic field analysis is used for predicting the performance of an induction motor and a slip-ring generator having different faults implemented in their structure. Virtual measurement data provided by the numerical magnetic field analysis are analysed using modem signal processing techniques to get a reliable indication of the fault. Support vector machine based classification is applied to fault diagnostics. The stator fine current, circulating currents between parallel stator branches and forces between the stator and rotor are compared as media of fault detection.
引用
收藏
页码：969 / 981
页数：13
相关论文
共 50 条
  • [21] Fault classification in gears using Support Vector Machines (SVMs) and signal processing
    Soleimani, Ali
    Mahjoob, Mohammad J.
    Shariatpanahi, Masoud
    2009 FIFTH INTERNATIONAL CONFERENCE ON SOFT COMPUTING, COMPUTING WITH WORDS AND PERCEPTIONS IN SYSTEM ANALYSIS, DECISION AND CONTROL, 2010, : 25 - 28
  • [22] Research on Machinery Fault Diagnostics Based on Vibration Signal Analysis
    Lv Yan
    Fang Liqing
    Zhang Qiantu
    PROCEEDINGS OF THE 2015 INTERNATIONAL SYMPOSIUM ON MATERIAL, ENERGY AND ENVIRONMENT ENGINEERING (ISM3E 2015), 2016, 46 : 580 - 583
  • [23] Analysis of fault detection in the electrical insulation system of rotating machines
    Cimino, Alessandro
    Jenau, Frank
    Staubach, Christian
    Mashkin, Andrey
    Pohlmann, Friedhelm
    2018 INTERNATIONAL CONFERENCE ON DIAGNOSTICS IN ELECTRICAL ENGINEERING (DIAGNOSTIKA), 2018,
  • [24] Advances in Diagnosis of Electrical Machines Through External Magnetic Field
    Pusca, Remus
    Romary, Raphael
    PROCEEDINGS OF THE 2015 7TH INTERNATIONAL CONFERENCE ON ELECTRONICS, COMPUTERS AND ARTIFICIAL INTELLIGENCE (ECAI), 2015, : P5 - P12
  • [25] Magnetic Field around Asynchronous Electrical Machines with Variable Frequency
    Diaz, Felipe
    Deniz, Fabian
    Hernandez, Guillermo
    ELECTROMAGNETIC FIELD, HEALTH AND ENVIRONMENT, PROCEEDINGS OF EHE '07, 2008, 29 : 38 - 42
  • [26] Vibration signal analysis for electrical fault detection of induction
    Su, Hua
    Xi, Wang
    Chong, Kil To
    2007 INTERNATIONAL SYMPOSIUM ON INFORMATION TECHNOLOGY CONVERGENCE, PROCEEDINGS, 2007, : 188 - +
  • [27] Numerical Calculation of Magnetic Fields as a Basis for the Design of Electrical Machines.
    Budig, Peter-Klaus
    Pohl, Andreas
    Wagner, Manfred
    Mueller, Duerte-Susanne
    Wissenschaftliche Zeitschrift - Technische Hochschule Karl-Marx-Stadt, 1986, 28 (03): : 407 - 421
  • [28] Online Fault Diagnosis of Large Electrical Machines using Vibration Signal-A Review
    Sadeghi, Iman
    Ehya, Hossein
    Faiz, Jawad
    Ostovar, Hossein
    2017 INTERNATIONAL CONFERENCE ON OPTIMIZATION OF ELECTRICAL AND ELECTRONIC EQUIPMENT (OPTIM) & 2017 INTL AEGEAN CONFERENCE ON ELECTRICAL MACHINES AND POWER ELECTRONICS (ACEMP), 2017, : 470 - 475
  • [29] Fault Diagnostics of Wind Turbine Drive-Train using Multivariate Signal Processing
    Maheswari, R. Uma
    Umamaheswari, R.
    INTERNATIONAL JOURNAL OF ACOUSTICS AND VIBRATION, 2019, 24 (02): : 334 - 342
  • [30] Fault diagnostics of wind turbine drive-train using multivariate signal processing
    Uma Maheswari R.
    Umamaheswari R.
    International Journal of Acoustics and Vibrations, 2019, 24 (02): : 334 - 342
12345