Condition Monitoring and Diagnosis of Switching Power Facility Based on Mechanical Characteristics

Switching facilities such as on-load tap changer, circuit breaker, and disconnecting switch are important components in power system, mechanical failures account for over 70% of their faults. Therefore, condition monitoring and fault diagnosis based on mechanical characteristics have significant meaning for improving the stability of apparatus and the reliability of power supplement. This paper dealt with the condition monitoring techniques of signal sensing, data acquisition, signal processing and analysis methods for condition assessment and diagnosis for switching power facilities. An acceleration sensor is used for detecting the vibration signal and current sensors are used for measuring the tripping coil current, closing coil current, and driving current of motor. Signal processing and analysis methods include envelope analysis based on Hilbert transform and wavelet transform, similarity analysis, energy distribution cure, and time-frequency analysis are proposed as diagnosis strategy for switching facilities. From the field test, it is verified that the proposed methods and strategy can effectively diagnose the condition of on-load tap changer, circuit breaker, and disconnecting switch. In addition, condition monitoring and diagnosis based on mechanical characteristics is suitable for online monitoring and has advantages of electrical contactless measurement, high safety, reliability, and efficiency.