The Cutty Sark is undergoing major conservation to slow down the deterioration of the original Victorian fabric of the ship. The conservation work being carried out is “state of the art” but there is no evidence at present for predictions 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 restoration is completed. This paper presents the prognostics framework being developed using three prognostics approaches: Physics-of-Failure (PoF) models, Data-driven methods and a fusion approach integrating both former approaches. “Canary” and “Parrot” devices have been designed to mimic the actual mechanisms that would lead to failure of the iron structures. 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 which could lead to failures. 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. As a demonstration, PoF models and MD analysis are applied to a pair of “canary” and “parrot” devices for which corrosion data was generated using temperature, humidity and time as the factors causing corrosion.
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materials damage prognostics, materials degradation, prognostic fusion, remaining useful life (RUL)
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