基于自动化技术的10kV配电线路故障检测系统设计

Design of 10 kV Distribution Line Fault Detection System Based on Automation

针对配电线路故障检测与诊断问题,设计一套基于自动化技术的智能故障检测系统。该系统采用边云协同计算架构和多Agent智能决策框架,通过深度学习、知识图谱等算法,实现故障的精准诊断、快速定位和自适应隔离,平均定位误差不超过30 m,隔离时间小于140 ms。实验结果表明,该系统能在毫秒级时间尺度内实现故障检测、定位、隔离与恢复的全流程自动化处理,提升配电网的智能化水平和供电可靠性。

This paper presents an intelligent fault detection system based on automation technology for distribution line fault detection and diagnosis.The system adopts an edge-cloud collaborative computing architecture and a multi-agent intelligent decision-making framework,utilizing algorithms such as deep learning and knowledge graphs to achieve precise fault diagnosis,rapid localization,and adaptive isolation,with an average localization error not exceeding 30 m and isolation time less than 100 ms.Experimental results demonstrate that the system can achieve fully automated processing of fault detection,localization,isolation,and recovery within millisecond time scales,thereby enhancing the intelligence level of distribution networks and improving power supply reliability.