Deep Learning-Based Explanations for Remaining Useful Life Prediction of Aircraft Turbofan Engines

Description

Presented at the ICCBMA 2024, this study focuses on predictive maintenance strategies for aircraft turbofan engines. Utilizing advanced deep learning architectures, including CNNs and LSTMs, the research accurately models engine degradation trajectories. To enhance interpretability, XAI methods like SHAP and LIME were integrated, offering valuable insights for high-stakes aviation contexts.

Period	11 Sept 2024
Event title	International Conference for CBM in Aerospace
Event type	Conference
Location	ParisShow on map
Degree of Recognition	International