Implementation of ground-based lightning locating system using particle swarm optimization algorithm for lightning mapping and monitoring
Cloud-to-ground (CG) lightning is a natural phenomenon that poses significant threats to human safety, infrastructure, and equipment. The destructive impacts of lightning strikes on humans and their property have been a longstanding concern for both society and industry. Countries with high thunders...
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| Format: | Article |
| Language: | English |
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MDPI
2023
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| Online Access: | http://eprints.utm.my/106669/1/MazlanHashim2023_ImplementationofGroundBasedLightning.pdf |
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| author | Mehranzamir, Kamyar Pour, Amin Beiranvand Abdul Malek, Zulkurnain Afrouzi, Hadi Nabipour Alizadeh, Seyed Morteza Hashim, Mazlan |
| author_facet | Mehranzamir, Kamyar Pour, Amin Beiranvand Abdul Malek, Zulkurnain Afrouzi, Hadi Nabipour Alizadeh, Seyed Morteza Hashim, Mazlan |
| author_sort | Mehranzamir, Kamyar |
| collection | ePrints |
| description | Cloud-to-ground (CG) lightning is a natural phenomenon that poses significant threats to human safety, infrastructure, and equipment. The destructive impacts of lightning strikes on humans and their property have been a longstanding concern for both society and industry. Countries with high thunderstorm frequencies, such as Malaysia, experience significant fatalities and damage due to lightning strikes. To this end, a lightning locating system (LLS) was developed and deployed in a 400 km2 study area at the University Technology Malaysia (UTM), Johor, Malaysia for detecting cloud-to-ground lightning discharges. The study utilized a particle swarm optimization (PSO) algorithm as a mediator to identify the best location for a lightning strike. The algorithm was initiated with 30 particles, considering the outcomes of the MDF and TDOA techniques. The effectiveness of the PSO algorithm was found to be dependent on how the search process was arranged. The results of the detected lightning strikes by the PSO-based LLS were compared with an industrial lightning detection system installed in Malaysia. From the experimental data, the mean distance differences between the PSO-based LLS and the industrial LLS inside the study area was up to 573 m. Therefore, the proposed PSO-based LLS would be efficient and accurate to detect and map the lightning discharges occurring within the coverage area. This study is significant for researchers, insurance companies, and the public seeking to be informed about the impacts of lightning discharges. |
| first_indexed | 2024-09-24T00:03:14Z |
| format | Article |
| id | utm.eprints-106669 |
| institution | Universiti Teknologi Malaysia - ePrints |
| language | English |
| last_indexed | 2024-09-24T00:03:14Z |
| publishDate | 2023 |
| publisher | MDPI |
| record_format | dspace |
| spelling | utm.eprints-1066692024-07-14T09:36:22Z http://eprints.utm.my/106669/ Implementation of ground-based lightning locating system using particle swarm optimization algorithm for lightning mapping and monitoring Mehranzamir, Kamyar Pour, Amin Beiranvand Abdul Malek, Zulkurnain Afrouzi, Hadi Nabipour Alizadeh, Seyed Morteza Hashim, Mazlan Q Science (General) TK Electrical engineering. Electronics Nuclear engineering Cloud-to-ground (CG) lightning is a natural phenomenon that poses significant threats to human safety, infrastructure, and equipment. The destructive impacts of lightning strikes on humans and their property have been a longstanding concern for both society and industry. Countries with high thunderstorm frequencies, such as Malaysia, experience significant fatalities and damage due to lightning strikes. To this end, a lightning locating system (LLS) was developed and deployed in a 400 km2 study area at the University Technology Malaysia (UTM), Johor, Malaysia for detecting cloud-to-ground lightning discharges. The study utilized a particle swarm optimization (PSO) algorithm as a mediator to identify the best location for a lightning strike. The algorithm was initiated with 30 particles, considering the outcomes of the MDF and TDOA techniques. The effectiveness of the PSO algorithm was found to be dependent on how the search process was arranged. The results of the detected lightning strikes by the PSO-based LLS were compared with an industrial lightning detection system installed in Malaysia. From the experimental data, the mean distance differences between the PSO-based LLS and the industrial LLS inside the study area was up to 573 m. Therefore, the proposed PSO-based LLS would be efficient and accurate to detect and map the lightning discharges occurring within the coverage area. This study is significant for researchers, insurance companies, and the public seeking to be informed about the impacts of lightning discharges. MDPI 2023-05 Article PeerReviewed application/pdf en http://eprints.utm.my/106669/1/MazlanHashim2023_ImplementationofGroundBasedLightning.pdf Mehranzamir, Kamyar and Pour, Amin Beiranvand and Abdul Malek, Zulkurnain and Afrouzi, Hadi Nabipour and Alizadeh, Seyed Morteza and Hashim, Mazlan (2023) Implementation of ground-based lightning locating system using particle swarm optimization algorithm for lightning mapping and monitoring. Remote Sensing, 15 (9). pp. 1-30. ISSN 2072-4292 http://dx.doi.org/10.3390/rs15092306 DOI:10.3390/rs15092306 |
| spellingShingle | Q Science (General) TK Electrical engineering. Electronics Nuclear engineering Mehranzamir, Kamyar Pour, Amin Beiranvand Abdul Malek, Zulkurnain Afrouzi, Hadi Nabipour Alizadeh, Seyed Morteza Hashim, Mazlan Implementation of ground-based lightning locating system using particle swarm optimization algorithm for lightning mapping and monitoring |
| title | Implementation of ground-based lightning locating system using particle swarm optimization algorithm for lightning mapping and monitoring |
| title_full | Implementation of ground-based lightning locating system using particle swarm optimization algorithm for lightning mapping and monitoring |
| title_fullStr | Implementation of ground-based lightning locating system using particle swarm optimization algorithm for lightning mapping and monitoring |
| title_full_unstemmed | Implementation of ground-based lightning locating system using particle swarm optimization algorithm for lightning mapping and monitoring |
| title_short | Implementation of ground-based lightning locating system using particle swarm optimization algorithm for lightning mapping and monitoring |
| title_sort | implementation of ground based lightning locating system using particle swarm optimization algorithm for lightning mapping and monitoring |
| topic | Q Science (General) TK Electrical engineering. Electronics Nuclear engineering |
| url | http://eprints.utm.my/106669/1/MazlanHashim2023_ImplementationofGroundBasedLightning.pdf |
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