As the key transmission equipment of high-speed trains, high-voltage vehicle cable terminals face the combined action of electricity, heat, humidity and other external factors during the actual operation of the train, and are prone to form air gap defects on the surface of the main insulation, thereby causing partial discharge (PD) which seriously affect the safety of the train. PD detection method is one of the most effective methods for evaluating insulation condition. This paper builds a PD test platform to conduct high-frequency PD tests on vehicle cable terminals. Based on the average discharge amplitude of the pulse current signal, number of discharges（within one cycle） and pulse phase distribution, the process from the start of PD to the breakdown of the insulation is studied. The results show that the PD of the vehicle cable terminal caused by the air gap defect can be divided into four levels: normal state, attention state, early warning state and warning state. In addition, based on the characteristic parameters such as the average discharge amplitude, number of discharges and pulse phase distribution of the pulse current signal, the fuzzy C mean clustering (FCM) analysis method is proposed to automatically diagnose and evaluate the severity of PD.

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