Correlation between Insulation Degradation and Partial Discharge Characteristics under Accelerated Electrical Aging

Date

2026-8-14

Author

Alipour Vahid Sadabad, Pouya

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Partial discharge (PD) is among the earliest indicators of insulation degradation in high-voltage (HV) equipment, often the only warning before a defect in a transformer, cable, winding, or switchgear causes failure. Despite decades of research, no unified framework links PD signals to defect type and severity across discharge mechanisms. This thesis tries to solve this problem by studying corona, surface, internal, and interfacial discharge under controlled laboratory conditions using IEC 60270 methods. For each type, phase-resolved PD (PRPD) patterns and logarithmic magnitude distributions H(Q) are recorded, along with inception voltage (PDIV) and pulse amplitude behavior. Corona discharge, generated with a needle-plate electrode in a pressure-controlled enclosure, is examined versus voltage and pressure; inception and flashover voltages fall from about 3.9 kV and 14.5 kV at 76 cmHg to about 2.1 kV and 4.5 kV at 26 cmHg. Surface discharge, studied across electrode geometries and materials, shows continuity with corona rather than being a separate mechanism. Internal and interfacial discharge, linked to electrical tree growth, are examined via microscope imaging alongside pulse repetition rate and phase distribution, connecting signals to physical defect growth. The thesis proposes severity ratings based on discharge power and cumulative energy, finding a near-constant ratio of about 2.5 μm/pC between maximum discharge amplitude and tree length, with severity differing three- to elevenfold between internal and interfacial samples under equivalent conditions. It examines how well PRPD alone distinguishes discharge mechanisms and when combining PRPD, H(Q), and other features becomes necessary, ending with implications for condition-based maintenance and future work.

Subject Keywords

Electrical treeing, High-voltage insulation, Partial discharge, PRPD pattern, Weibull statistics

URI

https://hdl.handle.net/11511/120633

Collections

Graduate School of Natural and Applied Sciences, Thesis