Fault diagnosis approach based on fuzzy probabilistic SDG model and Bayesian inference

The fault diagnosis approach based-on signed directed graph(SDG) has better completeness and explanation facility ,but it has some disadvantages due to lack of the quantitative information, so the semi-quantitative fault diagnosis approach based on model of fuzzy probabilistic SDG and Bayesian inference is proposed, the node variable was expressed as fuzzy variable with the more information, the cause-effect relationship between the nodes was described by conditional probabilities table (CPT), the set of failure source candidates is found out by Bayesian inference and backtracking algorithm, Furthermore, the candidates in the set are ranked according to the rate of fault possibility. The primary electrical power supply system in certain a satellite was modeled with the proposed approach, the diagnosis simulation results show that the diagnostic resolution can be improved significantly; the approach is feasible to be applied to on-board diagnosis for spacecraft.