Fusion approach for predictive maintenance of heritage structures

The Cutty Sark is undergoing major conservation to slow down the deterioration of the original Victorian fabric of the ship. While the conservation work being carried out is ¿state of the art¿, there is no evidence at present of the effectiveness of the conservation work 50 plus years ahead. A prognostics framework is being developed to monitor the ¿health¿ of the ship's iron structures to help ensure a 50 year life once conservation is completed with only minor deterioration taking place over time. This paper presents the prognostics framework being developed which encompasses four approaches: canary and parrot devices, physics-of-failure (PoF) models, precursor monitoring and data trend analysis and Bayesian networks. ¿Canary¿ and ¿parrot¿ devices have been designed to mimic the actual mechanisms that would lead to failure of the iron structures with canary devices failing faster to act as an indicator of forthcoming failures while parrot devices fail at the same rate as the structure under consideration. A PoF model based on decrease of corrosion rate over time is used to predict the remaining life of an iron structure. Mahalanobis distance (MD) is used as a precursor monitoring technique to obtain a single comparison metric from multiple sensor data to represent anomalies detected in the system. Bayesian network models integrating remaining life predictions from PoF models with information of possible anomalies from MD analysis are used to obtain more accurate predictions of remaining life. This paper describes why and how the four approaches are used for diagnostic and prognostics purposes and how they are integrated into the prognostics framework.