Artificial neural network application in an implemented lightning locating system

被引:3
|
作者
Mehranzamir, Kamyar [1 ]
Abdul-Malek, Zulkurnain [2 ]
Afrouzi, Hadi Nabipour [3 ]
Mashak, Saeed Vahabi [2 ]
Wooi, Chin-leong [4 ]
Zarei, Roozbeh [5 ]
机构
[1] Univ Nottingham Malaysia, Fac Sci & Engn, Dept Elect & Elect Engn, Jalan Broga, Semenyih 43500, Selangor, Malaysia
[2] Univ Teknol Malaysia, Fac Engn, Sch Elect Engn, Inst High Voltage & High Current, Johor Baharu, Malaysia
[3] Swinburne Univ Technol Sarawak, Fac Engn, Comp & Sci, Sarawak, Malaysia
[4] Univ Malaysia Perlis, Ctr Excellence Renewable Energy, Fac Elect Engn Technol, Pauh Putra Campus, Arau 02600, Perlis, Malaysia
[5] Deakin Univ, Sch Informat Technol, Melbourne, Vic, Australia
关键词
Lightning detection; Artificial neural network (ANN); Time difference of arrival (TDOA); Lightning discharge; PERFORMANCE; PREDICTION; CLOUD;
D O I
10.1016/j.jastp.2020.105437
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
Time difference of arrival (TDOA) technique is one of many bases to determine lightning strike location employed in a lightning locating system (LLS). In this technique, at least four measurement sensors are required to correctly locate a lightning strike. Usage of fewer number of sensors will result in non-unique solutions to the generated hyperbolas, and hence wrong lightning strike point. This research aims to correctly determine the strike point even if only three measuring sensors are utilized. An artificial neural network (ANN) based algorithm was developed for a 400 km(2) coverage area in Southern Malaysia using time of arrival data collected at the three measuring stations over a certain period. The Levenberg-Marquardt algorithm is demonstrated to correctly identify the lightning strike coordinates with an average error of 350 m. The algorithm has helped the three-station TDOA-based LLS to successfully locate the lightning strike point with a remarkable accuracy comparable to that of commercial systems.
引用
收藏
页数:26
相关论文
共 50 条
  • [21] Application of artificial neural network methods for the lightning performance evaluation of Hellenic high voltage transmission lines
    Ekonomou, L.
    Gonos, I. F.
    Iracleous, D. P.
    Stathopulos, I. A.
    ELECTRIC POWER SYSTEMS RESEARCH, 2007, 77 (01) : 55 - 63
  • [22] SEU experiments on an artificial neural network implemented by means of digital processors
    Velazco, R
    Assoum, A
    Cheynet, P
    Olmos, M
    Ecoffet, R
    IEEE TRANSACTIONS ON NUCLEAR SCIENCE, 1996, 43 (06) : 2889 - 2896
  • [23] Development and Application of Artificial Neural Network
    Yu-chen Wu
    Jun-wen Feng
    Wireless Personal Communications, 2018, 102 : 1645 - 1656
  • [24] Principle and application of artificial neural network
    Pan Xuhua
    PROCEEDINGS OF THE FIRST INTERNATIONAL SYMPOSIUM ON TEST AUTOMATION & INSTRUMENTATION, VOLS 1 - 3, 2006, : 1280 - 1283
  • [25] Development and Application of Artificial Neural Network
    Wu, Yu-chen
    Feng, Jun-wen
    WIRELESS PERSONAL COMMUNICATIONS, 2018, 102 (02) : 1645 - 1656
  • [26] Application of Artificial Neural Network in Engineering
    ZHANG Fan
    WANG Lei
    ZHOU Zhou
    ZHAO Jiaxin
    ZHANG Sensen
    HU Shixiang
    MA Wengang
    International Journal of Plant Engineering and Management, 2020, 25 (03) : 186 - 192
  • [27] Towards a global lightning locating system
    Said, Ryan
    WEATHER, 2017, 72 (02) : 36 - 40
  • [28] The analysis based on the artificial neural network in the application of the railroad ticketing system
    Fan, LL
    Wang, XG
    THIRD WUHAN INTERNATIONAL CONFERENCE ON E-BUSINESS: GLOBAL BUSINESS INTERFACE, 2004, : 158 - 165
  • [29] Application of an Artificial Neural Network for Measurements of Synchrophasor Indicators in the Power System
    Binek, Malgorzata
    Kanicki, Andrzej
    Rozga, Pawel
    ENERGIES, 2021, 14 (09)
  • [30] Application of Artificial Neural Network in Fluid Mechanics Teaching Evaluation System
    Zhu Changjun
    Zhou Jihong
    PROCEEDINGS OF 2008 INTERNATIONAL SEMINAR ON EDUCATION MANAGEMENT AND ENGINEERING, 2008, : 505 - 508