Reliability Assessment Technology for Spacial Complex Mechanical System

Abstract

Ground tests of spacial mechanical products have the characteristics of few test subsamples and expensive test cost, which often appear the cases of zero-failure samples. The classic reliability evaluation methods cannot adapt to the reliability assessment needs of small subsamples and zero-failure samples for high-reliability, long-life spacial complex mechanical products. The characteristics of failure rate functions of typical mechanical products such as mechanical structure, motors, bearings, gears, valves, and so on have been analyzed. Then the reliability evaluation methods of spacial complex mechanical system have been deduced, which has been combined the prior data of Bayesian method. Bayesian posterior distribution function of exponential distribution has been established by the method, which makes use of uniform distribution as a prior distribution, and combines with the convex characteristics of exponential distribution’s failure rate. Bayesian posterior distribution function of exponential distribution has been utilized in products, such as motors, valves, etc., which have characteristics of presenting exponential distribution. The evaluation range of accumulative failure-rate has been reduced by making use of accumulative failure-rate and predicted failure rate of exponential distribution And the weighted least-squares method has been used in parametric fitting based on accumulative failure-rate Then high-precision estimated failure rate of exponential distribution has been obtained. In this paper, the calculation example of compressor filled with spacial propellant has verified the feasibility of the calculation method. The problems of the reliability tests’ few subsamples and evaluating efficiency for expensive, complex spacial mechanical products have been solved effectively by the above proposed method.