Design, Implementation, and Testing of Partial Discharge Signal Pattern Recognition and Judgment System Application Using Statistical Method

被引:0
|
作者
Jannah, Roro Roudhotul [1 ]
Khayam, Umar [1 ]
机构
[1] Inst Teknol Bandung, Sch Elect Engn & Informat, Elect Power Engn Study Program, Bandung 40132, Indonesia
关键词
high voltage; partial discharge; partial discharge signal pattern recognition and judgment system; statistical method;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Partial discharge is a problem that often affects high voltage equipments. Early diagnosis system for partial discharge can minimize the risk that caused by partial discharge. One of the steps of partial discharge diagnosis is partial discharge signal pattern recognition and judgement system that play a role in determining the type and level of partial discharge, and one of the methods that can be used in this step is statistical method. In order to make data processing easier, partial discharge pattern recognition and signal judgement system with statistical methods can be done with the help of applications created using MATLAB software. The objective of this research is designing, implementating, and testing the application of partial discharge signal pattern recognition and judgment system, so the application can determine type and level of partial discharge. Application is created by using MATLAB software, and to determine level and type of partial discharge, this application can make and gather database, measure partial discharge and statistical parameter, and compare it with database using Kolmogorov-Smirnov test. This application consist of two main part: database making and partial discharge diagnosis. The result of this research is application can determine level and type of partial discharge with 83% accuracy.
引用
收藏
页码:314 / 318
页数:5
相关论文
共 50 条
  • [1] Design, Implementation, and Testing of Partial Discharge Signal Processing System
    Khayam, Umar
    Surandaka, Y. A.
    2016 2ND INTERNATIONAL CONFERENCE OF INDUSTRIAL, MECHANICAL, ELECTRICAL, AND CHEMICAL ENGINEERING (ICIMECE), 2016, : 175 - 179
  • [2] Design of Pattern Recognition Application of Partial Discharge Signals Using Artificial Neural Networks
    Lumba, Lunnetta Safura
    Khayam, Umar
    Maulana, Rian
    PROCEEDING OF 2019 INTERNATIONAL CONFERENCE ON ELECTRICAL ENGINEERING AND INFORMATICS (ICEEI), 2019, : 239 - 243
  • [3] A new method using ultrasonic for partial discharge pattern recognition
    Li, YQ
    Lu, FC
    Xin, BO
    Chen, ZY
    POWERCON 2002: INTERNATIONAL CONFERENCE ON POWER SYSTEM TECHNOLOGY, VOLS 1-4, PROCEEDINGS, 2002, : 1004 - 1007
  • [4] Extension Theory Based Partial Discharge Pattern Recognition using Statistical Operators
    Divyashree, V
    Sumathi, S.
    PROCEEDINGS OF THE 2015 INTERNATIONAL CONFERENCE ON POWER AND ADVANCED CONTROL ENGINEERING (ICPACE), 2015, : 409 - 412
  • [5] Acoustic detection of partial discharge using signal processing and pattern recognition techniques
    Swedan, A.
    El-Hag, A. H.
    Assaleh, K.
    INSIGHT, 2012, 54 (12) : 667 - 672
  • [6] A Partial Discharge Pattern Recognition Method Combining Graph Signal and Graph Convolutional Network
    Zhang Y.
    Zhu Y.
    Zhongguo Dianji Gongcheng Xuebao/Proceedings of the Chinese Society of Electrical Engineering, 2021, 41 (18): : 6472 - 6480
  • [7] Application of Adaptive Neuro Fuzzy Inference System to the Partial Discharge Pattern Recognition
    Guo, Canxin
    Zhang, Li
    Qian, Yong
    Huang, Chengjun
    Wang, Hui
    Yao, Linpeng
    Jiang, Xiuchen
    2009 IEEE INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTING AND INTELLIGENT SYSTEMS, PROCEEDINGS, VOL 2, 2009, : 729 - +
  • [8] Application of vector quantization to partial discharge pattern recognition
    Yang, Li-Jun
    Liao, Rui-Jin
    Sun, Cai-Xin
    Zhou, Tian-Chun
    Zhongguo Dianji Gongcheng Xuebao/Proceedings of the Chinese Society of Electrical Engineering, 2009, 29 (31): : 122 - 127
  • [9] Application of Fuzzy Logic for Partial Discharge Pattern Recognition
    Lumba, Lury Amatullah
    Khayam, Umar
    Lumba, Lunnetta Safura
    PROCEEDING OF 2019 INTERNATIONAL CONFERENCE ON ELECTRICAL ENGINEERING AND INFORMATICS (ICEEI), 2019, : 210 - 215
  • [10] Towards automated statistical partial discharge source classification using pattern recognition techniques
    Janani, Hamed
    Kordi, Behzad
    HIGH VOLTAGE, 2018, 3 (03): : 162 - 169