Computer and Modernization ›› 2024, Vol. 0 ›› Issue (10): 14-20.doi: 10.3969/j.issn.1006-2475.2024.10.003

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Grounding Grid Corrosion Localization Based on Improved Sparrow Search Algorithm

  

  1. (The PLA  Army Logistics Academy, Chongqing  401311, China)
  • Online:2024-10-29 Published:2024-10-30

Abstract: The grounding grid is an important component of the normal operation of the power system, the resistance value of the grounding grid is related to system stability, safety protection, and current setting directly. The materials of the grounding grid are mainly ordinary carbon steel or galvanized carbon steel and perennially underground which is prone to corrosion and failure. When the corrosion and failure of grounding grid happens, it is necessary to locate and repair corrosion faults timely. With the rapid development of electrical systems, the performance requirements of grounding grids have become stricter, which puts forward higher requirements for the precision and accuracy of grounding grid corrosion localization. In response to the current situation of low accuracy in locating corrosion of grounding grids, this article proposes an improved sparrow search algorithm for corrosion localization of grounding grids (INLSSA). The algorithm uses ICMIC chaotic mapping, integrates the northern goshawk optimization exploration phase position strategy, and incorporates Levy flight disturbances in the following phase to improve the sparrow search algorithm. We establish a fault diagnosis model based on electrical network theory and micro processing method. Finally, we use INLSSA algorithm for solution. The experimental results show that compared with sparrow search algorithm, northern goshawrk optimization algorithm, grey wolf optimizer, dung beetle optimizer, golden jackal optimization, INLSSA can effectively locate faults and has high stability and accuracy, which can be used as a reference for actual grounding grid corrosion location.

Key words: grounding grid, corrosion fault localization, improved sparrow search algorithm, INLSSA, micro processing method

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