RUL Prediction for Turbine Disc Based on High-Order Particle Filtering

Turbine disc is one of the most crucial parts in an aero-engine and it is also regarded as the vulnerable part which suffers from damage frequently. Remaining useful life (RUL) prediction technology is a useful tool to provide failure warnings and increase safety. For turbine disc, however, it is still a great challenge. This paper proposes a high-order particle filtering (HOPF)-based approach for RUL prediction of turbine disc. First, a turbine disc health indicator is constructed based on the unbalance vibration analysis. Then, an improved double exponential model is developed for turbine disc degradation modeling. Next, model updating and RUL prediction are carried out by the HOPF algorithm. The proposed approach is finally validated using the experimental data of a turbine disc. Satisfactory results demonstrate that the proposed approach performs well on turbine disc RUL prediction.