微型电脑应用2025，Vol.41Issue(5)：13-16,21,5.
基于粒子群算法的输电线路设备集中供电异常状态检测方法
Particle Swarm Optimization Algorithm Based Detection Method for Abnormal State of Centralized Power Supply of Transmission Line Equipment
摘要
Abstract
To improve the accuracy of abnormal state detection for transmission line equipment,this article designs a centralized power supply abnormal state detection method for transmission line equipment based on particle swarm optimization algorithm.The article designs an edge intelligent terminal for transmission line equipment to collect data related to abnormal state of cen-tralized power supply.A data missing repair model is constructed based on long short-term memory neural networks,permuta-tion entropy and ensemble empirical mode decomposition is used to repair missing data.An abnormal state detection algorithm is designed based on BP neural network and particle swarm optimization algorithm to achieve centralized power supply abnormal state detection for transmission line equipment.The test results show that the mean squared error of power supply abnormal state detection of the designed method is lower than 0.015 as a whole.When the number of abnormal states reaches 40,the number of iterations of the designed method is still less than 400.关键词
粒子群算法/输电线路设备/边缘智能设备/集中供电/BP神经网络/异常状态检测Key words
particle swarm optimization algorithm/transmission line equipment/edge intelligent device/centralized power sup-ply/BP neural network/abnormal state detection分类
信息技术与安全科学引用本文复制引用
张文锋,王洪武,杨腾..基于粒子群算法的输电线路设备集中供电异常状态检测方法[J].微型电脑应用,2025,41(5):13-16,21,5.基金项目
云南省中国南方电网项目(YNKJXM20220231) （YNKJXM20220231）
