首页|Decision Support System for Maintenance Management Using Bayesian Networks
Decision Support System for Maintenance Management Using Bayesian Networks
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国家科技期刊平台
NETL
NSTL
万方数据
维普
The maintenance process has undergone several major developments that have led to proactive considerations and the transformation from the traditional "fail and fix" practice into the "predict and prevent" proactive maintenance methodology. The anticipation action, which characterizes this proactive maintenance strategy is mainly based on monitoring, diagnosis, prognosis and decision-making modules. Oil monitoring is a key component of a successful condition monitoring program. It can be used as a proactive tool to identify the wear modes of rubbing parts and diagnoses the faults in machinery. But diagnosis relying on oil analysis technology must deal with uncertain knowledge and fuzzy input data. Besides other methods, Bayesian Networks have been extensively applied to fault diagnosis with the advantages of uncertainty inference; however, in the area of oil monitoring, it is a new field. This paper presents an integrated Bayesian network based decision support for maintenance of diesel engines.
decision support system, fault diagnosis, Bayesian Networks, oil monitoring
LIU Yan、LI Shi-qi
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School of Mechanical Science and Engineering, Huazhong Universityof Science and Technology, Wuhan 430074, P.R.China
国家科技期刊平台
NSTL
万方数据
维普
