电力信息与通信技术2025，Vol.23Issue(9)：35-41,7.DOI:10.16543/j.2095-641x.electric.power.ict.2025.09.05
基于改进分布参数模型和ELM的交叉互联电缆接地系统缺陷状态识别
Defect Status Identification of Cross-connected Cable Grounding System Based on Improved Distribution Parameter Model and ELM
摘要
Abstract
High-voltage cables are one of the main carriers for power transmission in power systems,and the stable and safe operation of their grounding system is crucial.However,the harsh operating environment and laying method brings many problems to the grounding system.To this end,this paper proposes a grounding system defect identification method based on an improved distribution parameter model and an extreme learning machine(ELM).First,the single-phase distribution parameter model is improved to make it suitable for cross-interconnected cables,and the fault characteristics are extracted based on the difference between the model calculated value and the sample value of the cable end shield.Then,an extreme learning machine prediction model is established through the feature data set.Finally,verification is performed based on the data set,and the results show that compared with other classification models,the accuracy of ELM for grounding system state recognition reaches 95.83%,which is 6.66%and 10.83%respectively compared with traditional radial basis and least squares support vector machine.The research method has good application prospects for the status monitoring and diagnosis of high-voltage cable grounding systems.关键词
交叉互联电缆/分布参数模型/极限学习机(ELM)/接地系统/缺陷识别Key words
cross-connected cable/distribution parameter model/extreme learning machine(ELM)/grounding system/defect identification分类
信息技术与安全科学引用本文复制引用
李昆晟,朱峻永,杨海龙,吴琛,张奇英,赵仲勇,罗建..基于改进分布参数模型和ELM的交叉互联电缆接地系统缺陷状态识别[J].电力信息与通信技术,2025,23(9):35-41,7.基金项目
国家电网有限公司科技项目"超高压公司2023年基于电缆精确模型高压电缆接地系统状态监测技术研究科技技术服务"(SGCQJX00DLJS2310467) （SGCQJX00DLJS2310467）
重庆市留学人员回国创业创新支持计划资助(cx2019123). （cx2019123）
