A Discussion on the Aging Mechanism and Life Prediction Method of Insulation in Low-Voltage Electrical Equipment

This study focuses on the accurate prediction of the insulation life of low-voltage electrical equipment, and its core work includes the analysis of insulation aging mechanisms, comparison of prediction methods, and the construction and verification of a coupled model. Through systematic analysis of the aging mechanisms of single factors (thermal, electrical, environmental, and mechanical), the nonlinear characteristics of multi-factor coupling and the logic for identifying dominant factors are clarified, revealing the coupling laws such as the positive feedback of thermal-electric "temperature rise-discharge" and the synergistic acceleration of hydrolysis by thermal and environmental factors. By comparing the performance differences between traditional Arrhenius equations and Weibull distributions with modern methods such as BP neural networks and LSTM, a multi-factor coupled prediction model integrating the weight allocation of the analytic hierarchy process and the synergistic effect function is proposed to quantify the impact of each factor and its coupling effect on insulation life. Using XLPE cable insulation layers and epoxy partitions of switchgear as examples, accelerated aging experiments with three factors (thermal, electrical, and humidity) are conducted to test macroscopic indicators such as dielectric loss factor and breakdown voltage, as well as microscopic parameters such as characteristic peaks in infrared spectroscopy and microcrack density. Experimental verification shows that the prediction accuracy of this coupled model is significantly better than traditional methods and single intelligent algorithms. Under the 110℃/0.8kV operating condition, RMSE and MAE are reduced by 68.4% and 71.0% respectively compared with the Arrhenius equation, and macroscopic performance degradation is strongly correlated with microstructure evolution (R²≥0.83). This study provides a technical solution with both theoretical depth and engineering practicality for the insulation life assessment of low-voltage electrical equipment.