Hu Zhaoyong, Qu Liangsheng
(School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an 710049, China)
Abstract:In order to solve the uncertainty problems in engineering diagnosis, a three-layered topological model using Bayesian diagnostic network was proposed based on condition,operation, fault, and symptom. Moreover, it used the superiority of Bayesian network in dealing with uncertainty and experts synthetically experience. The model represented the complicated relationships in engineering diagnosis intuitively. A practical example shows that its evidences for diagnosis are more sufficient and its result of network inference is more consistent with practice in comparison with naive Bayesian networks, because it takes account of operating actual conditions and operation records of equipment. This model has been used successfully for diagnosis of an industrial gas turbine in a refinery of a petro-chemical complex.
Keywords:Bayesian network; engineering diagnosis; uncertainty
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