A Novel Wavelet Assisted Neural Network for Transmission Line Fault Analysis

被引:0
|
作者
Bhowmik, P. S.
Purkait, P.
Bhattacharya, K.
机构
来源
PROCEEDINGS OF THE INDICON 2008 IEEE CONFERENCE & EXHIBITION ON CONTROL, COMMUNICATIONS AND AUTOMATION, VOL I | 2008年
关键词
Discrete Wavelet Transform; Fast Fourier Transform; Neural Network; Power System Faults;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this modern era, electric power has become the basic need for the business world. The quality and reliability of power needs to be maintained for obtaining optimum performance. Now-a-days power has also become a business commodity. Hence, faultless and lossless transmission and distribution of power is necessary. Power faults must be identified quickly from various sources (eg. information from relays etc.) and corrected as soon as possible. Advanced signal processing tools such as Discrete Wavelet Transform (DWT) can be used very effectively for parameterization and characterization of the fault signals. On the other hand, properly configured Neural Network (NN) can be utilized for classification of the faults based on the DWT signal. Presently Electromagnetic Transient Program (EMTP) is used for simulation of a model transmission system and DWT and NN is performed using MATLAB. Faults of various types at different locations along the transmission line have been simulated and attempts have been made to correctly identify and locate the fault.
引用
收藏
页码:223 / 228
页数:6
相关论文
共 50 条
  • [21] Fault Analysis of Controllable Series Compensated Transmission Line with Wavelet Transform and Support Vector Machine
    Vyas, Bhargav
    Maheshwari, Rudra Prakash
    Das, Biswarup
    3RD NIRMA UNIVERSITY INTERNATIONAL CONFERENCE ON ENGINEERING (NUICONE 2012), 2012,
  • [22] Transmission Line Fault Detection and Classification by using Wavelet MultiresolutionAnalysis: A Review
    Kunj, Tripti
    Ansari, M. A.
    Vishwakarrma, C. B.
    2018 INTERNATIONAL CONFERENCE ON POWER ENERGY, ENVIRONMENT AND INTELLIGENT CONTROL (PEEIC), 2018, : 607 - 612
  • [23] Fault Classification of a Transmission Line using Wavelet Transform & Fuzzy Logic
    Ray, Papia
    Mishra, Debani Prasad
    Mohaptra, Spandan
    PROCEEDINGS OF THE FIRST IEEE INTERNATIONAL CONFERENCE ON POWER ELECTRONICS, INTELLIGENT CONTROL AND ENERGY SYSTEMS (ICPEICES 2016), 2016,
  • [24] Fault Diagnosis of Rolling Bearing on the Basis of Wavelet Neural Network
    Lin, Wu Song
    Liu Jianxin
    Lili
    ADVANCED MATERIALS, MECHANICS AND INDUSTRIAL ENGINEERING, 2014, 598 : 244 - 249
  • [25] A Fault Detection Technique in Transmission Line By using Discrete Wavelet Transform
    Patel, Tapas Kumar
    Panda, Prafulla Chandra
    Swain, Sarat Chandra
    Mohanty, Subodh Kumar
    PROCEEDINGS OF THE 2017 IEEE SECOND INTERNATIONAL CONFERENCE ON ELECTRICAL, COMPUTER AND COMMUNICATION TECHNOLOGIES (ICECCT), 2017,
  • [26] Study of the Fault Diagnosis Based on Wavelet and Neural Network for the Motor
    Shao, Keyong
    Han, Lijuan
    Wang, Xinmin
    Zhang, Fengwu
    Qian, Kun
    ADVANCES IN MECHATRONICS AND CONTROL ENGINEERING II, PTS 1-3, 2013, 433-435 : 483 - +
  • [27] INU Fault Diagnosis Based on Genetic Wavelet Neural Network
    Luo, Yunlin
    Dai, Qingtian
    Wang, Li
    Wang, Kun
    26TH CHINESE CONTROL AND DECISION CONFERENCE (2014 CCDC), 2014, : 2837 - 2840
  • [28] Fault diagnosis and classification based on wavelet transform and neural network
    Hadad, Kamal
    Pourahmadi, Meisam
    Majidi-Maraghi, Hosein
    PROGRESS IN NUCLEAR ENERGY, 2011, 53 (01) : 41 - 47
  • [29] Application of wavelet package and neural network in ventilators fault warning
    Zhu Quan
    Fu Sheng
    Li Jing
    PROCEEDINGS OF 2008 INTERNATIONAL CONFERENCE ON CONDITION MONITORING AND DIAGNOSIS, 2007, : 1362 - 1364
  • [30] Wavelet neural network approach for fault diagnosis to a chemical reactor
    Wang, Dazhi
    Yang, Jie
    Liu, Xiaoqin
    Yang, Qing
    Wang, Kenan
    WCICA 2006: SIXTH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-12, CONFERENCE PROCEEDINGS, 2006, : 5764 - +