Abstract: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.