Bayesian Networks for Predicting Remaining Lifed.

Autor: Rosunally, Yasmine, Stoyanov, Stoyan, Bailey, Chris, Mason, Peter, Campbell, Sheelagh, Monger, George, Bell, Ian
Předmět:
Zdroj: International Journal of Performability Engineering; Sep2010, Vol. 6 Issue 5, p499-512, 14p, 1 Color Photograph, 4 Diagrams, 1 Chart, 6 Graphs
Abstrakt: 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. The framework encompasses four approaches: Canary and Parrot devices, Physics-of-Failure (PoF) models, Precursor Monitoring and Data Trend Analysis and Bayesian Networks. Bayesian network models are used to update remaining life predictions from PoF models with information from precursor monitoring. This paper presents the prognostics framework with focus on the Bayesian network approach used to improve remaining life predictions of Cutty Sark iron structures. [ABSTRACT FROM AUTHOR]
Databáze: Supplemental Index