A hybrid framework bifurcates RUL prediction for turbofan engines into healthy and degraded regimes via LSTM autoencoder state classification, using Weibull survival analysis and probabilistic neural networks with MC dropout for uncertainty-aware estimates on the C-MAPSS dataset.
Luca Biggio, Alexander Wieland, Manuel Arias Chao, Iason Kastanis, and Olga Fink
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Bifurcated Remaining Useful Life Prediction: A Hybrid Approach for Realistic Uncertainty Characterization
A hybrid framework bifurcates RUL prediction for turbofan engines into healthy and degraded regimes via LSTM autoencoder state classification, using Weibull survival analysis and probabilistic neural networks with MC dropout for uncertainty-aware estimates on the C-MAPSS dataset.