Research on expert diagnosis system for mechanical fault of high voltage circuit breaker based on fuzzy matrix and neural network technology

High voltage circuit breaker is an important equipment to protect the normal operation of power system. In this paper, based on the mechanical fault characteristics of the circuit breaker, a mechanical fault diagnosis expert system of high voltage circuit breaker has been developed using the fuzzy matrix algorithm and neural network technology. Expert database of the system is constructed on real-time online monitoring data and fault database, while extracting the feature signal of condition monitoring from online monitoring data and combining fault database, the system can diagnosis, analysis, and draw a conclusion through fuzzy matrix algorithm, with the RBF neural network as an auxiliary decision-making means. When the diagnosis conclusions of the two methods are identical, maintenance method would be suggested according to the concluded location of the fault. When there is a difference between the two conclusions, conclusion will be drew by further calculation and analysis with linear fitting rules. Through the experimental verification by various types of faults, the fault recognition accuracy of the system is effectively improved. The system could be applied to delivery test and field fault warning as well as maintenance work, providing support for circuit breakers from a regular maintenance to condition-based maintenance, which can be helpful to improve the reliability and economy of circuit breaker.