黑龙江科技大学学报2025，Vol.35Issue(1)：140-146,7.DOI:10.3969/j.issn.2095-7262.2025.01.021
PSO-ELM算法的井下漏电故障选线方法
Line selection method for underground leakage fault based on PSO-ELM algorithm
胥良 1何士刚1
作者信息
- 1. 黑龙江科技大学 电气与控制工程学院,哈尔滨 150022
- 折叠
摘要
Abstract
This paper seeks to investigate the method for the line selection underground leakage fault with the multi criteria fusion,and proposes a fault line selection method based on the particle swarm opti-mization algorithm optimizing the extreme learning machine(ELM).The study involves building a 1 140 V underground power supply system model by using Matlab/Simulink simulation software to obtain the reactive power characteristics,fundamental amplitude characteristics,and transient characteristics of the zero-sequence current signal for obtaining the fault measurement data by calculating the fault measure-ment function;inputting the ELM neural network model optimized by particle swarm optimization algo-rithm,and outputting the line selection results by training.The results show that this method has high ac-curacy and fast speed,and meets the requirements of reliability and speed for underground leakage fault line selection.关键词
漏电故障/粒子群算法/极限学习机/故障测度Key words
leakage fault/particle swarm optimization algorithm/limit learning machine/fault measures分类
矿业与冶金引用本文复制引用
胥良,何士刚..PSO-ELM算法的井下漏电故障选线方法[J].黑龙江科技大学学报,2025,35(1):140-146,7.
