Remaining Useful Life Prediction of Aero-Engine Based on KSFA-GMM-BID-Improved Autoformer
Jiashun Wei,
Zhiqiang Li,
Yang Li
et al.
Abstract:Addressing the limitation of traditional deep learning models in capturing the spatio-temporal characteristics of flight data and the constrained prediction accuracy due to sequence length in aero-engine life prediction, this study proposes an aero-engine remaining life prediction approach integrating a kernel slow feature analysis, a Gaussian mixture model, and an improved Autoformer model. Initially, the slow degradation features of gas path performance parameters over time are extracted through kernel slow … Show more
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