A novel approach towards parametric assessment of reliability and resilience of high voltage mica-based insulation systems by statistical analysis of experimental failure data

Abstract

Insulation systems in high-voltage electric machines play a pivotal role in the reliable operation and longevity of the equipment. Mica-based insulation materials have proven to possess and maintain excellent dielectric properties in the long run and prevent premature insulation degradation. Numerous qualifications tests, such as voltage endurance, are outlined in IEC and IEEE standards. The authors, however, take a different parametric approach, opting for reliability assessment of insulation systems using derived three-parameter Weibull models. Therefore, instead of simple pass–fail criteria, empirical data is employed to determine failure rate probabilities quantitatively and objectively. Experimental data, including breakdown, dissipation factor, and partial discharge measurements, are used to construct the Weibull distribution model to predict fault and failure rates and calculate hazard functions. The rigorous examinations interpreted through the analytical model help assess insulation system resilience and particularly the impact of electrical field stress and mica content. Variation of electrical stress from 66.75 to 71.20 V/mil demonstrated how the mean time to failure of the system changed from 146.4 to 85.1 at 3 U_n, hence identifying opportunities for design improvement and uncovering performance boundaries. Ultimately, the developed framework enhances comprehension of insulation system failure probabilities, guiding design decisions and ensuring a secure and reliable operation of electrical machines across applications.