Research on performance state evaluation of circuit breaker energy storage spring based on intelligent algorithm

Abstract

The performance state evaluation method of circuit breaker energy storage spring mainly judges its performance state indirectly by measuring the pre-tightening force or pre-pressure of the spring. However, there may be some errors in this indirect measurement method, which will affect the accuracy of the evaluation results. Therefore, the performance state evaluation based on intelligent algorithm is proposed. Select the evaluation characteristic quantity of performance state, calculate the energy storage spring impulse according to the momentum theorem, and obtain the pressure value of the closing energy storage spring through the pressure sensor as the evaluation quantity reflecting the energy storage spring performance state. The BP neural network is established, and the fireworks algorithm is applied to the BP neural network to optimize the initial weight and threshold, so as to realize the performance state evaluation of energy storage spring based on BP neural network. The experimental results show that the spring energy release speed of the proposed method is in the range of 0 - 1.0m/s, and the estimated spring pressure value is basically consistent with the actual value.