The Use of Multilayer Perceptron to Classify and Locate Power Transmission Line Faults

被引：6

作者：

Eboule, P. S. Pouabe ^{[1
]}

Hasan, Ali N. ^{[1
]}

Twala, Bhekisipho ^{[1
]}

机构：

[1] Univ Johannesburg, Dept Elect Engn Technol, POB 524 Auckland Pk, ZA-2006 Johannesburg, South Africa

来源：

ARTIFICIAL INTELLIGENCE AND EVOLUTIONARY COMPUTATIONS IN ENGINEERING SYSTEMS, ICAIECES 2017 | 2018年 / 668卷

关键词：

Faults location; Faults classification; Faults detection; MLP; Power transmission line;

D O I：

10.1007/978-981-10-7868-2_5

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper investigates the use of multilayer perceptron (MLP) technique for locating and detecting faults in a power transmission line. MLP was used twice in this paper to locate and to detect faults. The experiments were conducted on a 600-km-length, three-phase power transmission line data which include the required faults to detect and locate the fault. Matlab was used to perform the experiments. Results show that MLP achieved high prediction accuracy for fault type detection of 98% and a prediction accuracy of 78% for fault location.

引用

页码：51 / 58

页数：8

共 50 条

[1] Transmission Line Fault Detection Based on Multilayer Perceptron
Yang, Hengyu
2022 INTERNATIONAL CONFERENCE ON BIG DATA, INFORMATION AND COMPUTER NETWORK (BDICN 2022), 2022, : 778 - 781
[2] The Use of Machine Learning Techniques to Classify Power Transmission Line Fault Types and Locations
Hasan, Ali N.
Eboule, P. S. Pouabe
Twala, Bhekisipho
2017 INTERNATIONAL CONFERENCE ON OPTIMIZATION OF ELECTRICAL AND ELECTRONIC EQUIPMENT (OPTIM) & 2017 INTL AEGEAN CONFERENCE ON ELECTRICAL MACHINES AND POWER ELECTRONICS (ACEMP), 2017, : 221 - 226
[3] Machine Learning Embedded in Distribution Network Relays to Classify and Locate Faults
Jones, C. Birk
Summers, Adam
Reno, Matthew J.
2021 IEEE POWER & ENERGY SOCIETY INNOVATIVE SMART GRID TECHNOLOGIES CONFERENCE (ISGT), 2021,
[4] On the Use of Electromagnetic Time Reversal to Locate Faults in Series-Compensated Transmission Lines
Razzaghi, R.
Lugrin, G.
Paolone, M.
Rachidi, F.
2013 IEEE GRENOBLE POWERTECH (POWERTECH), 2013,
[5] DETECTION OF HIGH IMPEDANCE ARCING FAULTS USING A MULTILAYER PERCEPTRON
SULTAN, AF
SWIFT, GW
FEDIRCHUK, DJ
IEEE TRANSACTIONS ON POWER DELIVERY, 1992, 7 (04) : 1871 - 1877
[6] An alternate method to detect and classify the transmission line faults using Clarke's transformed currents
Velpula, Rajesh
Nagarajan, Madhan
Pitchaimuthu, Raja
ELECTRIC POWER SYSTEMS RESEARCH, 2024, 236
[7] Efficacy of Feature Selection Techniques for Multilayer Perceptron Neural Network to Classify Mammogram
Valarmathi, P.
Robinson, S.
2014 SIXTH INTERNATIONAL CONFERENCE ON ADVANCED COMPUTING, 2014, : 26 - 31
[8] A nonlinear equalization method based on multilayer perceptron for OFDM power-line communication
Luo, CF
Cheng, SJ
Xiong, L
Nguimbis, J
Zhang, YB
Ma, J
IEEE TRANSACTIONS ON POWER DELIVERY, 2005, 20 (04) : 2437 - 2442
[9] Incremental Power Improves Relay Selectivity to Transmission Line Faults
Kumar A.W.
Verma H.K.
Singh S.
Journal of The Institution of Engineers (India): Series B, 2019, 100 (01) : 61 - 68
[10] Prediction Interval of Cumulative Number of Software Faults Using Multilayer Perceptron
Momotaz, Begum
Dohi, Tadashi
APPLIED COMPUTING & INFORMATION TECHNOLOGY, 2016, 619 : 43 - 58

← 1 2 3 4 5 →