Study on prior information fusion method in reliability assessment for low-voltage switchgear

Reliability analysis of low-voltage switchgear is of great significance to the safety and high efficiency of power system and its equipment. However, this analysis cannot use the conventional reliability estimation method based on large sample theory. In this thesis, the author introduces Bayes theory into the reliability analysis of low voltage switchgear. Firstly, reliability growth model and expert information method are used to obtain prior information of unknown parameters. Secondly, data from the first step is transformed and converted to gain compatibility with field samples. Finally, we form a low-voltage switchgear´s prior information credibility test and multiple sources of prior information fusion method.