Feature extraction and severity assessment of partial discharge under protrusion defect based on fuzzy comprehensive evaluation

Partial discharge (PD) is an early manifestation of insulation fault that occurs in electrical equipment, which holds rich feature information used to insulation assessment. In this study, step voltage method was applied to investigate the PD development process of typical protrusion defects in gas-insulated switchgear. Nine features were extracted to represent the deterioration degree of internal insulation. Fuzzy C means clustering was applied to solve the state centres. PD severity was divided into four states based on the PD developing process, and the harmfulness of each state was illustrated. Finally, adaptive objective weight technology based on the theory of maximising deviation was adopted, and two-level fuzzy comprehensive evaluation (TL-FCE) model was established to address the problem of the weight allocation of different features on the evaluation result. The experimental test has been conducted to test the validity and effectiveness of the model. It is proved that TL-FCE owns good performance to assess PD severity, and it is more suitable to handle fuzzy boundary problems than support vector machine.