一种基于电机电流的高压断路器与负荷开关弹簧操作机构故障诊断算法

Fault Diagnosis Algorithm on Spring Operating Mechanism for High Voltage Circuit Breaker and Load Switch Based on Motor Current

为实现高压断路器与负荷开关的故障诊断,提高设备安全可靠性,有必要深入研究电机电流特性与高压断路器、负荷开关的弹簧操作机构状态之间的关系。由于传统BP神经网络存在易陷入局部最小点及网络收敛速度慢等缺陷,采用遗传算法对于BP神经网络进行优化可以提高判断准确率及诊断效率。诊断结果表明,GA-BP算法可以根据断路器、负荷开关电机电流数据快速准确判断设备所处的运行状态,且精确度高,对于工程实际具有广泛应用前景。

For achieving the fault diagnosis of high voltage circuit breaker and load switch as well as improve their safety and reliability,it is necessary to deeply study the relationship between motor current characteristics and the state of spring operating mechanism for high voltage circuit breaker and load switch.Since the traditional BP neural network has such defects as easily falling into local minimum points and slow network convergence speed,the use of genetic algorithm to optimize BP neural network can improve the judgment accuracy and diagnosis efficiency.The diagnosis results show that GA-BP algorithm can quickly and accurately judge the operating state of the equipment in accordance with the current data of of motor for the circuit breaker and load,has high accuracy and wide application prospect for engineering practice.