Daming Lin

TL;DR: This paper attempts to summarise and review the recent research and developments in diagnostics and prognostics of mechanical systems implementing CBM with emphasis on models, algorithms and technologies for data processing and maintenance decision-making.

TL;DR: In this paper, the fault growth parameter (FGP) from the residual error signal was calculated using the proportional-hazards modelling technique and several statistical and replacement decision models were built based upon the observed condition data and ensuing failure events.

TL;DR: This paper proposes the application of a principal components proportional hazards regression model in condition-based maintenance (CBM) optimization and describes the main issues and problems in using the proposed methodology.

TL;DR: In this paper, the availability of a system subject to hidden failure inspected at constant interval with both non-negligible downtime due to inspection and non-negative downtime for repair/replacement is considered.

TL;DR: In this paper, a model for multiple degradation features of an individual component is introduced and a proportional hazards model is presented, which considers hard failures and multiple degradation feature simultaneously, to predict the mean remaining useful life of a component based on on-line degradation information.