Abstract:

In the maintainability index verification by the Bayesian small sample method, to solve the problem that the prior maintainability information and on-site repair information are very likely different populations, the inner product model that the repair time information in the prior test stage converts into on-site repair information and the linear model that the similar equipment repair time information converts into that of the equipment which is ready to be evaluated are established. The random weighting method is used to convert a piece of prior information into a prior distribution. With the on-site information being considered as the standard, and according to the discrepancy degree between the mean parameter of each prior information distribution and that of the onsite information distribution model, the weight of the prior distribution is determined. Then by calculating the probability density errors between the integrated prior distribution and the hypothetic normal distribution, the hypothesis that the fused integrated prior distribution is normal distribution is tested, and the method to accurately calculate the distribution parameters is also put forward. Prior maintainability information conversion and fusion of some ship equipment shows that the method is effective.