Adaptive Maintenance Scheme for Degrading Devices With Dynamic Conditions and Random Failures

The estimations of degradation and remaining useful life are important for realizing the maintenance of modern devices, which generally operate under varying conditions. Although some prognostic approaches have been presented, there is still a lack of an effective maintenance scheme that utilizes prognostic information to maintain systems under varying operational conditions. Therefore, a new degradation-integrated failure model is presented in this article for deteriorating systems that are subject to dynamic conditions and random failures. An adaptive maintenance scheme is then developed on the basis of the failure model. The proposed scheme is used to adaptively monitor the system conditions and switch the monitoring frequency according to the system hazard level. The monitoring frequencies in the maintenance scheme are optimized by a computational algorithm formulated in a semi-Markov decision process framework using estimated conditional reliability under varying conditions. The particularity of this work is the consideration of a changeable monitoring scheme under dynamic conditions, which is effective in reducing false alarms of maintenance incurred by environmental shocks. The proposed approach is demonstrated by a case study of power devices, and comparisons with other advanced approaches are also presented.