Abstract:

The reliability life data analysis is an important basis of reliability engineering. Two main problems are still unsolved in this field: one is that the probability distribution selected by experience depends heavily on the people’s subject judgment, and so can not ensure its applicability; the other is that the usual probability distributions can not meet the need of life time data fit in many instances because their fit abilities are limited. To solve the two problems, firstly this paper gives the denseness proof of the proposed Gamma mixture. Secondly,a general reliability life data fit method,which is based on the denseness of Gamma mixture,is proposed.For the Gamma mixture parameter estimation,an algorithm of expectation maximization(EM) type is developed.To illustrate the effectiveness of the method proposed,six examples are used.Finally,the WP-7 aviation engine's I-class blade failure data analysis is taken as the application example to compare the proposed method with the conventional ones.

Key words: reliability , engineering,  , life , data,  , denseness,  , mixture , of , Gamma , distributions,  , EM , algorithm