| Smart grid is developing rapidly with the promotion of artificial intelligence(AI)technology,and online condition assessment of circuit breaker(CB),as one of the most important facility in power system,is increasingly requested.Aiming at the frequent faults in circuit breakers,this paper studies the causes of failure and diagnosis methods of CBs.A set of circuit breaker monitoring system is designed and developed in combination with embedded technology.The main works of this paper are as follows:1)Fault analysis and summary of circuit breakers.From the structure and working principle of the operating mechanism and energy storage mechanism of the circuit breaker,the phenomena and reasons of the fault of the circuit breaker are analyzed and summarized.The relationship between the fault and the characteristic information of the circuit breaker components is expounded,and the knowledge base of the fault diagnosis algorithm of the circuit breaker is built.2)Research on fault diagnosis method of circuit breaker.In order to transform the sampled information into a circuit breaker feature library that can be used for fault diagnosis,a data preprocessing method based on filtering algorithm and feature information extraction algorithm is introduced in this paper.In order to diagnose the mechanical failure of the circuit breaker,a mechanical fault diagnosis algorithm based on empirical mode decomposition and vibration energy entropy is introduced in this paper.In order to improve the effectiveness of the fault diagnosis algorithm of the actuator,a fault diagnosis algorithm based on Bayesian theory is proposed in this paper.3)Soft-ware design of fault diagnosis device for high voltage circuit breaker.Based on the above theory and method,a circuit breaker fault diagnosis system is developed,and the detailed design of circuit breaker data monitoring model,data preprocessing model,fault diagnosis model and circuit breaker historical status query model are given. |
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