Abstract
Inspection equipment needs to collect a large amount of data in the process of inspection, and its size and battery are limited, so computing power becomes the main factor restricting the efficient inspection of inspection equipment. In this article, an optimized moving edge computing technology for electric power inspection is proposed, and an inspection path planning model based on particle swarm optimization (PSO) algorithm is constructed and the problem is solved, so as to realize the global path planning of electric power equipment inspection. Finally, the simulation test is carried out, and the simulation results show that with the increase in the number of experiments, the accuracy of the proposed method is stable at about 95.2%; Moreover, the simulation running time of the algorithm is short, which is about 0.5 s lower than the traditional support vector machine (SVM) algorithm on average. Compared with the conventional PSO algorithm, the improved PSO algorithm accords with the idea of distributed computing. When multiple individual nodes enter the parallel computing state at the same time, the transmission and running speed of information parameters are greatly promoted, and the heuristic search behavior makes the results not fall into the local optimal solution state, which is convenient for the accurate derivation of the global optimal solution.
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Acknowledgement
This work is supported by the National Key R&D Program of China (2020YFB0906000, 2020YFB0906001) and Science and Technology Project of Guizhou Power Grid Co., Ltd. (GZKJXM20200720).
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Zhou, Y., **n, M., Xu, C. (2024). Research on an Optimized Moving Edge Computing Technology for Power Patrol Inspection. In: Hu, C., Cao, W. (eds) Conference Proceedings of the 2023 3rd International Joint Conference on Energy, Electrical and Power Engineering. CoEEPE 2023. Lecture Notes in Electrical Engineering, vol 1208. Springer, Singapore. https://doi.org/10.1007/978-981-97-3940-0_84
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DOI: https://doi.org/10.1007/978-981-97-3940-0_84
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