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Simulation study on Multi-UAV leak source detection in large and medium-sized chemical plant areas
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Xuefeng Zhang1, Jingjing Tang2, Jun Jiang3, **, Di Chen1
China Safety Science Journal | 2026, 36(5) : 56 - 63
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China Safety Science Journal | 2026, 36(5): 56-63
• Safety Technology and Engineering •
Simulation study on Multi-UAV leak source detection in large and medium-sized chemical plant areas
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Xuefeng Zhang1, Jingjing Tang2, Jun Jiang3, **, Di Chen1
Affiliations
  • 1 School of Computer Science and Technology, Anhui University of Technology, Ma'anshan Anhui 243000, China
  • 2 Department of Asset and Laboratory Management, Anhui University of Technology, Ma'anshan Anhui 243000, China
  • 3 Tongling Nonferrous Metals Co., Ltd., Tongling Anhui 244000, China
Published: 2026-05-28 doi: 10.16265/j.cnki.issn1003-3033.2026.05.1091
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In order to address frequent hazardous gas leaks in large and medium-sized chemical plant areas, this study proposes a leak source localization method based on a multi-strategy improved PSO(MSPSO) algorithm, leveraging the collaborative capabilities of a small number of UAVs. First, considering the physical constraints UAVs face during actual movement, an acceleration control strategy was integrated into PSO algorithm. Simultaneously, the chemical plant area was divided into distinct zones to more accurately simulate the UAVs' flight states during the search process. Second, an upwind search strategy was introduced based on diffusion characteristics of leak sources, utilizing wind direction information to accelerate the search process. Third, to prevent UAVs from getting stuck in pseudo-leak sources, Cauchy mutation perturbations and simulated annealing mechanisms were employed to enhance the UAVs' ability to escape local optima. Finally, a three-dimensional simulation environment for large and medium-sized chemical plant areas was established to compare and analyze the performance of various swarm intelligence algorithms in simulated scenarios. The results indicate that MSPSO exhibits faster convergence and higher localization success rates, with performance better meeting the leakage source localization requirements of large-to-medium-scale chemical plant areas.

large and medium-sized chemical plants  /  unmanned aerial vehicles(UAV)  /  particle swarm optimization(PSO)  /  leak source localization  /  active olfaction
Xuefeng Zhang, Jingjing Tang, Jun Jiang, Di Chen. Simulation study on Multi-UAV leak source detection in large and medium-sized chemical plant areas[J]. China Safety Science Journal, 2026 , 36 (5) : 56 -63 . DOI: 10.16265/j.cnki.issn1003-3033.2026.05.1091
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Article Info
doi: 10.16265/j.cnki.issn1003-3033.2026.05.1091
  • Receive Date：2026-01-14
  • Online Date：2026-06-26
  • Published：2026-05-28
Article Data
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History
  • Received：2026-01-14
  • Revised：2026-03-19
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Affiliations
    1 School of Computer Science and Technology, Anhui University of Technology, Ma'anshan Anhui 243000, China
    2 Department of Asset and Laboratory Management, Anhui University of Technology, Ma'anshan Anhui 243000, China
    3 Tongling Nonferrous Metals Co., Ltd., Tongling Anhui 244000, China
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