On-load tap-changer (OLTC) is an important part of large-scale load transformers, and its fault will directly affect the reactive power flow regulation of the power system and the stability of the load center voltage. In this paper, a fault state diagnosis method based on vibration signal is proposed for fault diagnosis of tap changer. The vibration signals are decomposed by wavelet packet transform and calculated energy entropy to obtain the state information of the tap changer. The experimental data shows that the state characteristics are obvious under different faults, which lays a foundation for in-depth study of fault diagnosis.

On-Load Tap-Changer is an important device with high failure rate in power systems. This paper proposes an improved EMD energy spectrum feature extraction method based on vibration signals. It divides the entire OLTC shifting process into two sections, and extracts their characteristic energy spectrum. Analysis of sample data shows that this method can more effectively distinguish the state of OLTC.

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