Electrical Equipment Lifetime Distribution Analysis

With the development of economy and the improvement in life quality of the people in our country, the requirement to the electric energy quality of user has been more and more rigorous. Accordingly higher requirement to reliability of electric power system has been put forward.. Especially with the issuance and implementation of the electric power law of P.R.C and the initiation of professed service of power industry, the reliability of electric power system plays a increasingly important part in power production and management. As important parts of power system , electrical equipments play a crucial role in the production, transmission and distribution of electrical energy. For example , transformer is the hinge of transforming voltage and exchanging power. With the advancing of the voltage and increasingly complex of the network, the function of the transformer is more and more important in power system. Its operation in safety and reliability directly influence the security of the power system. So it's very significant to evaluate the reliability of electrical equipment to improve the reliability of the power system.The life curve of the electrical equipment is different from life curve of the electronic product and it disobeys the exponential distribution. The thesis studies the actual operation activity of a certain transformer. In the thesis we only count the failure that leads the transformer to quit operation, regarding the transformer as Non-repairable system whose main index is failure rate. The thesis puts forward the method to process the data and count the failure rate. After primary dealing with the data, we can think that the transformer were put into operation at the same time though actually they were not so. Through analyzing the data, the thesis gets the dispersed points of failure rate and then calculates reliability function and the type of life distribution. The Levenberg-Marquardt method is used to realize optimal parameter estimation of the failure rate function, and the strict boundary which specifically distinguishes different phases of the failure rate are effectively determined.