江西科学2025，Vol.43Issue(3)：514-517,524,5.DOI:10.13990/j.issn1001-3679.2025.03.17
基于改进BP神经网络的开关柜故障智能检测研究
Research on Intelligent Fault Detection of Switchgear Based on An Improved BP Neural Network
摘要
Abstract
During long-term operation,high-voltage switchgear is susceptible to various mechanical faults.If these faults are not handled in time,they will not only affect the normal operation of the equipment,but also cause major safety accidents.In order to address this issue,this study proposes an intelligent fault detection method for switchgear based on an improved BP neural network.First,partial discharge fault signal features are extracted as the basis for developing an improved BP neural network fault diagnosis model.Next,through the construction of the fault diagnosis model,it can better adapt to the complex switchgear fault detection tasks.Finally,the improved BP neural network model undergoes training and learning to achieve intelligent recognition and fault detection for switchgear.The experimental results show that compared with the other two methods,the improved BP neural network significantly improves fault identification accuracy in intelligent switchgear fault detection.关键词
电力系统/机械故障/故障检测/开关柜/改进BP神经网络Key words
power system/mechanical fault/fault detection/switchgear/improve BP neural network分类
政治法律引用本文复制引用
孙旭,熊剑,程瑞剑,邱伊键,朱德明,刘琦..基于改进BP神经网络的开关柜故障智能检测研究[J].江西科学,2025,43(3):514-517,524,5.基金项目
2022年度江西省科学院省级科技计划项目包干制试点示范项目一般项目(2022YSBG22022). （2022YSBG22022）
