A Kalman Filter-Based Ensemble Approach With Application to Turbine Creep Prognostics

作者：Baraldi Piero^*; Mangili Francesca; Zio Enrico

来源：IEEE Transactions on Reliability, 2012, 61(4): 966-977.

DOI：10.1109/TR.2012.2221037

• Creep
• ensemble
• Kalman filter
• prognostics and health management

The safety of nuclear power plants can be enhanced, and the costs of operation and maintenance reduced, by means of prognostic and health management systems which enable detecting, diagnosing, predicting, and proactively managing the equipment degradation toward failure. We propose a prognostic method which predicts the Remaining Useful Life (RUL) of a degrading system by means of an ensemble of empirical models. The RUL predictions of the individual models are aggregated through a Kalman Filter (KF)-based algorithm. The method is applied to the prediction of the RUL of turbine blades affected by a developing creep.

• 出版日期2012-12