An online detection method for the mechanical fault of circuit breakers of rural distribution lines based on continuous wavelet transform and vibration signal characteristics

Abstract Rural distribution lines are widely distributed and dispersed, involving numerous circuit breaker equipment. Detecting mechanical faults on each circuit breaker requires significant time and human resources. It can bring significant interference and power outage risks to the operation of the line. Therefore, an online detection method is studied for mechanical faults in rural distribution line circuit breakers. Continuous wavelet transform technology is used to extract the characteristics of circuit breaker vibration signals. This feature is used to locate the faulty section. The PNN neural network is introduced to identify fault feature samples and achieve online detection of mechanical faults. To test the application performance of this method, a comparative experiment is designed. The results verified that when using this method to extract the vibration signal of circuit breaker mechanical faults, the error is low, and the fault detection accuracy is high.