故障树和人工神经网络在可靠性再分配中的应用

在产品可靠性设计过程中,通常情况下,可靠性指标的分配并不是一次可以完成的,不同的设计阶段有不同的可靠性分配方法。随着设计过程的深入,初步分配的结果可能会存在不合理的情况,所以在设计阶段中后期,还需要对可靠性指标进行再次分配。在进行指标分配之前,用一定的算法将所有最小割集进行筛选,再将筛选出的需要分配的最小割集利用人工神经网络进行指标分配,最终目标是将可靠性指标分配到故障树的最小割集或基本事件上。通过分配前初始可靠性与分配后的可靠性对比,可以找出产品设计中的薄弱环节进而改进设计,并在一定程度上检验了FMECA(failure mode,effects and criticism analysis,故障模式、影响及危害性分析)的结果。

The application of FTA and ANN in reliability reallocation

In the process of product reliability design,usually,the distribution of reliability index is not completed in one time.Different design stages have different reliability allocation methods.With the deepening of the design process,the results of the preliminary distribution may be unsatisfactory,so it's necessary to re-allocate the reliability index in middle and late stages.Prior to the index allocation,all the minimal cut sets are classified by a certain algorithm,and then the selected minimum cut sets to be allocated are distributed by using an artificial neural network (ANN).The ultimate goal is to allocate the reliability index to the minimal cut sets or elementary events of fault tree.By comparing the initial reliability before distribution and the reliability after distribution,we can find out the weak points in product design and then improve the design,which examines the results of FMECA (failure mode,effects and criticism analysis) to some extent.