A fault diagnosis model for embedded software based on FMEA/FTA and bayesian network

Failure modes and effects analysis (FMEA) and fault tree analysis (FTA) are two effective fault analysis technologies and the integration of them is also applied widely in many industry domains. But when they are used for fault diagnosis, the ability of inference is not very enough and especially they are not suitable to use the fault related symptoms to do some posterior inference. To solve this problem, this paper combines FMEA and FTA based on Bayesian Network (BN) to form a fault diagnosis analysis model. Case study shows that this model has a good FMEA/FTA fusion ability and posterior inference ability for embedded software fault diagnosis.