Abstract

Objective of this paper is to introduce a new technology known as prognostics and health management (PHM) which enables a real-time life prediction for safety critical systems under extreme loading conditions. In the PHM, Bayesian framework is employed to account for uncertainties and probabilities arising in the overall process including condition monitoring, fault severity estimation and failure predictions. Three applications - aircraft fuselage crack, gearbox spall and battery capacity degradation are taken to illustrate the approach, in which the life is predicted and validated by end-of-life results. The PHM technology may allow new maintenance strategy that achieves higher degree of safety while reducing the cost in effective manner.

Keywords

• Prognostics and Health Management;
• Prognostics;
• Reliability;
• Uncertainty Quantification;
• Bayesian Theory;
• Condition Based Maintenance;
• Fatigue Crack;
• Wind Turbine Gear Box;
• Battery