TY - GEN
T1 - RUL Prediction for Turbine Disc Based on High-Order Particle Filtering
AU - Fu, Yang
AU - Cao, Hongrui
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/10/15
Y1 - 2020/10/15
N2 - 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.
AB - 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.
KW - degradation modeling
KW - high-order particle filtering
KW - remaining useful life
KW - turbine disc
UR - https://www.scopus.com/pages/publications/85098549735
U2 - 10.1109/ICSMD50554.2020.9261721
DO - 10.1109/ICSMD50554.2020.9261721
M3 - 会议稿件
AN - SCOPUS:85098549735
T3 - International Conference on Sensing, Measurement and Data Analytics in the Era of Artificial Intelligence, ICSMD 2020 - Proceedings
SP - 215
EP - 220
BT - International Conference on Sensing, Measurement and Data Analytics in the Era of Artificial Intelligence, ICSMD 2020 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 1st International Conference on Sensing, Measurement and Data Analytics in the Era of Artificial Intelligence, ICSMD 2020
Y2 - 15 October 2020 through 17 October 2020
ER -