Fault diagnostic in power system using wavelet transforms and neural networks

被引：39
|
作者：
Charfi, F. [1 ]
Sellami, F. [1 ]
Al-Haddad, K. [2 ]
机构：
[1] Lab Elect & Technol Informat, Sfax, Tunisia
[2] Ecole Technol Super, Montreal H3C 1K3, PQ, Canada
来源：
2006 IEEE INTERNATIONAL SYMPOSIUM ON INDUSTRIAL ELECTRONICS, VOLS 1-7 | 2006年
关键词：
power device; faults; wavelet transform; neural network;
D O I：
10.1109/ISIE.2006.295798
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper presents a new approach to Fault detection and diagnosis in power system. Discrete wavelet transformations (DWT) combined with neural networks (NN) have been applied to a typical three phase inverter. A set of faults have been examined, such as inverter IGBT open-circuit fault, leg open fault. The input signals of this algorithm are the three-phase stator currents. Identification and classification uses approximation and details at levels 6 of these currents. The results of simulation show that the proposed technique can accurately detect identify and classify effectively the faults of interest in the power system.
引用
收藏
页码：1143 / 1148
页数：6
相关论文
共 50 条
  • [1] Classification of power system faults using wavelet transforms and probabilistic neural networks
    Kashyap, KH
    Shenoy, UJ
    [J]. PROCEEDINGS OF THE 2003 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS, VOL III: GENERAL & NONLINEAR CIRCUITS AND SYSTEMS, 2003, : 423 - 426
  • [2] Classification of Power System transients using wavelet transforms and Probabilistic Neural Networks
    Ramaswamy, S
    Kiran, BV
    Kashyap, KH
    Shenoy, UJ
    [J]. IEEE TENCON 2003: CONFERENCE ON CONVERGENT TECHNOLOGIES FOR THE ASIA-PACIFIC REGION, VOLS 1-4, 2003, : 1272 - 1276
  • [3] Power System Fault Detection and Classification Using Wavelet Transform and Artificial Neural Networks
    Malla, Paul
    Coburn, Will
    Keegan, Kevin
    Yu, Xiao-Hua
    [J]. ADVANCES IN NEURAL NETWORKS - ISNN 2019, PT II, 2019, 11555 : 266 - 272
  • [4] Reaction force inspection system using wavelet transforms and neural networks
    Yamada, Y
    Komura, Y
    Masuda, M
    Ookubo, Y
    [J]. 2002 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION, VOLS I-IV, PROCEEDINGS, 2002, : 2563 - 2566
  • [5] Wind Power Forecasting Using Wavelet Transforms and Neural Networks with Tapped Delay
    Saroha, Sumit
    Aggarwal, S. K.
    [J]. CSEE JOURNAL OF POWER AND ENERGY SYSTEMS, 2018, 4 (02): : 197 - 209
  • [6] Optimization of Artificial Neural Networks using Wavelet Transforms
    N. Vershkov
    M. Babenko
    A. Tchernykh
    V. Kuchukov
    N. Kucherov
    N. Kuchukova
    A. Yu. Drozdov
    [J]. Programming and Computer Software, 2022, 48 : 376 - 384
  • [7] Optimization of Artificial Neural Networks using Wavelet Transforms
    Vershkov, N.
    Babenko, M.
    Tchernykh, A.
    Kuchukov, V.
    Kucherov, N.
    Kuchukova, N.
    Drozdov, A. Yu.
    [J]. PROGRAMMING AND COMPUTER SOFTWARE, 2022, 48 (06) : 376 - 384
  • [8] Fault diagnosis of nonlinear analog circuits using neural networks with wavelet and Fourier transforms as preprocessors
    Aminian, F
    Aminian, M
    [J]. JOURNAL OF ELECTRONIC TESTING-THEORY AND APPLICATIONS, 2001, 17 (06): : 471 - 481
  • [9] Fault Diagnosis of Nonlinear Analog Circuits Using Neural Networks with Wavelet and Fourier Transforms as Preprocessors
    Farzan Aminian
    Mehran Aminian
    [J]. Journal of Electronic Testing, 2001, 17 : 471 - 481
  • [10] Wavelet Transforms for Fault Detection using SVM in Power Systems
    Sevakula, Rahul K.
    Verma, Nishchal K.
    [J]. IEEE INTERNATIONAL CONFERENCE ON POWER ELECTRONICS, DRIVES AND ENERGY SYSTEMS (PEDES 2012), 2012,
12345