Research on the Vehicle Fault Diagnosis base on the Fuzzy Dependability Algorithm

Abstract

This paper focuses on automobile failure detection and diagnostic accuracy, which have always been a hot research issue at home and abroad. Considering the deficiency of so many traditional fault diagnosis algorithms which failed to tell the complex relationship between the fault phenomenon and the reasons, and resulted in inaccurate fault diagnosis, this article proposed a new fault diagnosis of maximizing fuzzy dependability based on fuzzy rough set theory. This method could evaluate vehicle faults according to the dependency degree of condition attribute and calculate the probability of vehicle faults in line with fuzzy dependency degree. On this basis, the result will list out specific steps of fault diagnosis. Theoretical analysis and simulation experiments have proved the efficiency of this method on vehicle fault diagnosis. It could improve the reliability of fault monitoring.