Fault diagnosis for nonlinear mechatronic system using particle swarm optimization

This paper deals with the fault diagnosis of nonlinear mechatronic system using bond graph and particle swarm optimization. The mechatronic system under investigation includes a DC motor with a load part. Nonlinear phenomena such as friction and backlash are considered in the monitored system. The objective of fault diagnosis is to determine the fault source and estimate its magnitude. In order to realize the task in the application, the bond graph modeling tool is adopted to carry out fault detection and isolation. After the potential faults that could lead to the observed fault symptom are obtained, the particle swarm optimization is utilized for fault estimation purpose. Numerical simulations are performed to illustrate the effectiveness of the developed method.