电机电流—振动—旋转角度多特征分析的真空有载分接开关故障诊断研究OA

Fault diagnosis of on-load tap-changer(OLTC)is an important measure to ensure the safe operation of transformers.In this paper,the positive and negative pulse waveforms of motor currents,the rotation angle and vi-bration signals during the OLTC switching process of the OLTC is analyzed through the detection of the motor cur-rent,rotation angle of the transmission shaft,and three vibration signals of the vacuum on-load tap changer(OLTC)for a 110 kV transformer.The Butterworth high-pass filter and time-frequency domain analysis are used for signal processing.A variety of such characteristic parameters as amplitude,mean value,maximum/minimum value,ampli-tude average value in frequency domain and centroid frequency are extracted.Based on multiple information fea-tures analysis such as electrical,vibration,and angular,a vacuum OLTC mechanical fault diagnosis method based on random forest is proposed.The fault diagnosis results under normal operating conditions,different degrees of looseness in the drive shaft and loose arc resistors are obtained.The degree of looseness fault of transmission shaft(slight/serious)is quantitatively determined.The identification accuracy of fault category is higher than 95%.The fault simulation and multi-information feature-based diagnostic method proposed in this paper is of great signifi-cance for the state detection and fault diagnosis of OLTC.