Applications of Bayesian Network in Fault Diagnosis of Braking Deviation System

Abstract

Braking deviation system is an important piece of automotive operating equipment, targeting on the problems of complex fault mechanisms of automotive hydraulic braking system and uncertainty between fault type and fault symptoms, the method of Bayesian network fault diagnosis in baking deviation system has been raised. In the learning process of Bayesian network structure, this algorithm adopts statistical strategy for the rule library provided by many experts, discard rules with relatively weak casual relationship, and retain rules with stronger causal relationship, thereby set up the fault diagnosis hierarchical structure model in braking deviation system based on Bayesian network. Experimental data analysis shows that the Bayesian network fault diagnosis model has higher accuracy than fuzzy logic diagnosis method, effectively solving the uncertainties in fault diagnosis.