Online fault recognition of electric power cable in coal mine based on the minimum risk neural network

被引：0
|
作者：
汪梅 [1 ,2 ]
STATHAKI Tania [2 ]
机构：
[1] School of Electric and Control Engineering,Xi'an University of Science and Technology,Xi'an 710054,China
[2] Department of Electrical and Electronic Engineering,Imperial College,London SW7 2AZ,United Kingdom
来源：
International Journal of Coal Science & Technology | 2008年 / 14卷 / 03期
关键词：
minimum risk; neural network; traveling wave entropy; zero-order component; online cable; recognition algorithm; early fault;
D O I：
暂无
中图分类号：
TD61 [矿山输电与配电];
学科分类号：
0819 ;
摘要：
Firstly,the concepts of the traveling wave entropy and the feature function of traveling wave entropy were defined.Then the statistic characters of the traveling wave entropy feature function,mean value and variance were analyzed after the zero-order component of the traveling wave of online cable was selected to serve as the observed object.Finally,the new recognition algorithm of minimum risk neural network was pre- sented.The simulation experiments show that the recognitions of the early fault states can be completed correctly by using the proposed recognition algorithm.The classes of cable faults include in 1-phase ground faults,and the 2-phase short circuit faults or ground faults and the 3-phase short circuit faults or ground faults,open circuit.The fault resistance range is 1×10-1～1×109Ω.
引用
收藏
页码：492 / 496
页数：5
相关论文
共 50 条
  • [21] Prediction and Evaluation of Coal Mine Coal Bump Based on Improved Deep Neural Network
    Gong, Shuang
    Tan, Yi
    Wang, Wen
    GEOFLUIDS, 2021, 2021
  • [22] A New Fault Diagnosis Model of Electric Power Grid Based on Rough Set and Neural Network
    Zhang Liying
    Wang Dazhi
    Zhang Cuiling
    Liu Xiaoqin
    2012 FOURTH INTERNATIONAL CONFERENCE ON MULTIMEDIA INFORMATION NETWORKING AND SECURITY (MINES 2012), 2012, : 405 - 408
  • [23] Electric Power Grid Fault Diagnosis Based on Rough Radial Basis Function Neural Network
    Li, Xiao-quan
    Ke, Yan
    Chen, Geng
    2ND INTERNATIONAL CONFERENCE ON APPLIED MECHANICS, ELECTRONICS AND MECHATRONICS ENGINEERING (AMEME), 2017, : 46 - 51
  • [24] Model Identification of Coal Main Fans in Mine Based on Neural Network
    Du, Xinhui
    An, Ruifeng
    Chen, Zhimei
    ARTIFICIAL INTELLIGENCE AND COMPUTATIONAL INTELLIGENCE, PT III, 2011, 7004 : 178 - 185
  • [25] Study on Evaluation of Coal Mine Safety Based on BP Neural Network
    Guo, Kai
    EBM 2010: INTERNATIONAL CONFERENCE ON ENGINEERING AND BUSINESS MANAGEMENT, VOLS 1-8, 2010, : 3313 - 3316
  • [26] Roof Pressure Prediction in Coal Mine Based on Grey Neural Network
    Wang, Ke
    Zhuang, Xinwei
    Zhao, Xiaohu
    Wu, Wanrong
    Liu, Bing
    IEEE ACCESS, 2020, 8 : 117051 - 117061
  • [27] PREDICTION OF COAL MINE GAS CONCENTRATION BASED ON CONSTRUCTIVE NEURAL NETWORK
    Zhang, Yueqin
    Zeng, Qianqian
    3RD INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY AND COMPUTER SCIENCE (ITCS 2011), PROCEEDINGS, 2011, : 210 - 213
  • [28] Coal Mine Safety Investment Prediction Based on Wavelet Neural Network
    Ning Yuncai
    Chen Xiang
    2009 SECOND INTERNATIONAL CONFERENCE ON FUTURE INFORMATION TECHNOLOGY AND MANAGEMENT ENGINEERING, FITME 2009, 2009, : 242 - 245
  • [29] Neural Network Based Algorithm and Simulation of Information Fusion in the Coal Mine
    ZHANG, Xiao-qiang
    WANG, Hui-bing
    YU, Hong-zhen
    Journal of China University of Mining and Technology, 2007, 17 (04): : 595 - 598
  • [30] Neural Network Based Algorithm and Simulation of Information Fusion in the Coal Mine
    ZHANG Xiao-qiang 1
    Journal of China University of Mining & Technology, 2007, (04) : 595 - 598
12345