A dynamic maintenance policy based on prognostic for a single-unit system under indirect condition monitoring
Abstract
This work deals with a dynamic maintenance policy based on prognostic for a single-unit deteriorating system. In order to take a step forward to practice, the system is assumed operating under indirect condition monitoring. The degradation of system is described by a crack growth evolution modelled by the Paris-Ergodan law, and a non-destructive ultrasonic technique is used to monitor the system condition. A procedure of state estimation and prediction of values associated with system health from the noisy measured data are performed thanks to the well-known particle filter algorithm. Then based on these estimated/predicted value, a dynamic maintenance policy is developed and is compared with two more classical policies (i.e. block replacement or periodic inspection/replacement). The comparison results on the optimal expected maintenance cost rate will show the performance of the proposed dynamic maintenance.