A Reliability Model of Intelligent Station Secondary Device Based on Log-Normal Distribution Model and Its Discriminating Method

Abstract

Secondary device of intelligent station has long lifetime and high reliability due to its digital characteristics. The lifetime model of different equipment may obey distinct distributions. But at present, there are few discussions on the reliability model identification of secondary relay protection devices in China. The Log-Normal model and the Weibull model are very adaptable to data due to their flexibility. They are widely used in lifetime prediction and are easy to mix in analysis. This confusion may cause severe consequences when looking for low-percentile life reliability and focusing on equipment aging performance parameters. In this paper, we first establish a lifetime model for the intelligent station secondary equipment that conforms to the Log-Normal distribution model. Then we discriminate diverse models using the maximum likelihood function method. Finally we use the least squares method and the average rank method for parameter estimation. The proposed discriminating method avoids mutual transformation between nonlinear and linear, the identification result is accurate and clear, and the model parameter estimation method is simple.