Condition Assessment of Switchgear Cable Joints Based on Proportional Hazards Model

Cable joints are critical yet vulnerable components in switch cabinets, and improving their operational reliability remains a priority. We propose a state evaluation method based on the proportional hazards model (PHM). Given that the time-dependent failure rate of switch cabinet cable joints follows a Weibull distribution, we establish the PHM by integrating historical failure records with real-time condition monitoring data. We employ the ARMA model to forecast future failure rate trends. The residual series, defined as the discrepancy between predicted failure rates and actual values derived from the PHM, serves as a diagnostic metric. Using the central limit theorem, we determine an adaptive threshold interval that dynamically adapts to state variations in cable joints. Maintenance intervention is recommended when prediction errors exceed this statistically derived threshold. Finally, we validate the method’s efficacy through empirical operational data from cable joint systems.