Mechanical life prognosis of high voltage circuit breakers based on support vector machine

Abstract

Mechanical fault is one of the main faults occurring during the life cycle of high-voltage circuit breakers (HVCBs), which has a significant influence on the reliability of the electrical power system. In this paper, the mechanical prediction algorithm for HVCBs based on support vector machine (SVM) was studied. Firstly, we used a sliding time window (STW) method to extract features of the travel curves of the movable contacts and coil current curves of HVCBs. Then the historic data were used to learn a support vector regression machine and finally to predict the new curves. In the end, the mechanical life experiment data of a HVCB were applied to validate the feasibility of the algorithm. The results showed that the proposed algorithm could predict the mechanical condition of HVCBs successfully.

Publication
11th International Conference on Natural Computation (ICNC) (Zhangjiajie, China)
Date