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A Stochastic Methodology for Prognostics Under Time-Varying Environmental Future Profiles

A Stochastic Methodology for Prognostics Under Time-Varying Environmental Future Profiles

This video was recorded at NASA Conference on Intelligent Data Understanding (CIDU) 2011, Mountain View, CA. We present a stochastic model of a sensor-based degradation signal for predicting, in real time, the residual lifetime of individual components subjected to a time-varying environment. We consider future environmental profiles that evolve in a deterministic manner. Unique to our model is the union of historical data with real time sensor-based data to update the degradation model and the residual life distribution (RLD) of the component within a Bayesian framework. The performance of our model is evaluated based on degradation signals from both numerical experiments and a case study using real bearing data. The results show that our approach provides more accurate estimates of the... Show More
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