真空断路器状态监测及故障诊断研究

Research on Status Monitoring and Fault Diagnosis of Vacuum Circuit Breaker

针对电力系统中真空断路器采用人工定期巡检排查故障,存在人工劳动强度大、故障处理不及时、引发停电事故等问题,本文研究了人工智能技术、粒子群算法和BP神经网络,设计了一种真空断路器状态监测及故障诊断系统,对真空断路器运行状态实时监测及进行故障诊断。实验结果表明:系统运行稳定可靠,实时监测真空断路器运行状态,为电网运行风险预警提供指导,具有良好的应用价值。

In response to the problems of manual regular inspection and troubleshooting of vacuum circuit breakers in the power system,such as high labor intensity,untimely fault handling,and power outage accidents,this paper studies artificial intelligence technology,particle swarm optimization algorithm,and BP neural network,and designs a vacuum circuit breaker status monitoring and fault diagnosis system to monitor and diagnose the operating status of vacuum circuit breakers in real time.The experimental results show that the system runs stably and reliably,monitors the operating status of vacuum circuit breakers in real time,provides guidance for power grid operation risk warning,and has good application value.