Study on characteristics of health monitoring and critical warning based on partial discharge signals during the growth of electrical trees

Abstract

Partial discharge (PD) induces degradation in filament-like channels of electrical trees (ETs), leading to a significant reduction in material strength and lifespan. To enhance the assessment of insulation status in polyethylene (PE) based on PD characteristics during ET growth, a dynamic health monitoring evaluation model is developed. This model enables early critical warnings for insulation states. Findings reveal that during the rapid growth phase of ETs, the Dynamic Health Index of PE fluctuates within the range of [62%, 11%], with a failure rate reaching 54.30%. The transition point from the retardation stage to the rapid growth stage is identified as the critical warning threshold for insulation failure based on PD characteristics during ET growth. Utilizing linear fitting slopes of apparent discharge magnitude and ultra-high frequency amplitude in the time domain, the frequency bandwidth of ultra-high frequency signals, and average energy distribution facilitates effective differentiation between the retardation and rapid growth stages of ETs. This work establishes a robust foundation for developing an intelligent insulation state evaluation system, thereby enhancing the reliable operation of insulation systems.