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.