Bayesian based Fault Identification for Nonlinear Mechatronic System with Backlash

This article attempts to solve the problem of fault identification of nonlinear mechatronic system with backlash. The fault detection and isolation are carried out by evaluating the residuals and the fault signature matrix derived from the bond graph model of the system. In order to refine the fault candidates set after fault isolation, a Bayesian method is adopted where the potential faults in the fault candidates set are treated as the special states to facilitate the unknown parameters estimation. According to the estimation results, the true faults can be obtained which are useful for further maintenance purpose. Simulation studies are conducted to validate the proposed method.