Fault Diagnosis of Rolling Bearing Based on Bayesian Network and Fuzzy Evaluation - MA De-zhong; REN Suo; LIU Kai-xin; LI Ming; ZHOU Zhen (Journal of Harbin University of Science and Technology)
In the process of diagnosing large and complex system, the existing methods mainly improve the diagnosis effect by a series of methods, but lack the consideration of the difficulty of detection, the detection speed and the detection economy.In this paper, Bayesian network diagnosis and multi-factor fuzzy comprehensive evaluation are combined to diagnose the fault. In the process of diagnosis, not only the probability of failure is considered, but also the difficulty of detection, the speed of detection, the accuracy and economy of detection, and the optimization method is obtained.The advantages of this method in the comprehensive diagnosis process can be clearly seen by the example of diagnosing the fault of gearbox bearing.The research results can be used as an optimization method for fault diagnosis of large and complex systems, so as to guide the maintenance plan scientifically.