Coulomb and viscous friction fault detection with application to a pneumatic actuator

Generally, fault detection is the process of monitoring a physical dynamic system accompanied by conformation and assessment of any degradation of system performance. These systems are modelled and terms that are representative of a specific fault are identified and monitored for detection. In this paper, a fault detection algorithm is developed to isolate and detect friction changes in a high precision positioning mechanism. The designed fault detection algorithm addresses dynamic model estimation, dynamic filtering and recursive parameter estimation techniques to monitor online friction changes. The procedure is illustrated on a high precision servo pneumatic cylinder that drives a translational air bearing apparatus, designed to permit the addition of friction. Side loading of the cylinder rod induced by a friction fault causes significant loss of performance in these applications. It therefore serves to design a simple and effective online fault detection and isolation scheme for the designed experimental set-up.