A study on intelligent fault diagnosis in engine room by Bayes method

Traditional monitoring equipment can only give warning when a fault was detected. This paper focuses on an intelligent fault diagnosis system in an engine room. By using the anteriority Bayes data fusion and statistical inference method, we can build a fault knowledge base and inference rules, and predict and fast diagnose causes of the fault. This method of intelligent diagnosis is suitable to those equipments that have their own fault regulations. The article also applies these theories into practices in an engine room.