State-based Prognostics with State Duration Information of Cracks in Structures

Prognostics is a key process of Condition-Based Maintenance (CBM) having the ability to forecast the expected future performance of the system/component by calculating its Remaining Useful Life (RUL) under degradation process. This paper presents a state-based prognostic method using state duration information to predict the fatigue life or fatigue crack growth in structures. The process of implementing the proposed prognostics algorithm consists of the following two stages: The first stage is identifying the health state of the system, while the second stage is calculating the expected RUL. The presented prognostic method is applied on the Virkler fatigue crack growth dataset and results show that the method efficiently predicts the remaining useful life of aluminium test specimens under constant amplitude fatigue load cycles.