Estimation of a Stress-Strength Insulation Reliability Model by means of a New Bayes Method

A key role for the reliability model identification of the electrical insulation of power system components is played by adequate ageing models. This is the case of the popular “Stress-Strength” models, where “Strength” is the electrical endurance of the insulation and “Stress” is the applied stress magnitude. It is well known that reliability estimation may be better achieved, instead that using limited lifetime data, by the knowledge of the degradation mechanisms. The stress considered is the voltages surges which act on the insulation of a high voltage cable used in power systems. In order to exploit the flexibility of the Inverse Burr distribution as an Extreme value Distribution, the paper has the purpose of setting up a Stress-Strength insulation reliability model when both Stress and Strength follow Inverse distributions. Then, a practical Bayesian approach is proposed for the estimation of the model. The efficiency of the proposed Bayesian approach is verified by means of numerical simulations referred to real insulation data.