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
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