Remaining Useful Life Prediction Method of Aero Engines Based on Stacking Multi-model Fusion

BAI Weiwei; YANG Zhiyu; WANG Xiaomin; CHAI Jin

doi:10.7643/ issn.1672-9242.2026.05.007

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Equipment Environmental Engineering ›› 2026, Vol. 23 ›› Issue (5) : 53-63. DOI: 10.7643/ issn.1672-9242.2026.05.007

Aviation and Aerospace Equipment

Remaining Useful Life Prediction Method of Aero Engines Based on Stacking Multi-model Fusion

BAI Weiwei¹, YANG Zhiyu², WANG Xiaomin¹, CHAI Jin¹

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Abstract

The work aims to address the issue of insufficient generalization ability of a single model in predicting the remaining useful life (RUL) of aero engines. A remaining useful life prediction method of aero engines based on Stacking multi-model fusion was proposed. Firstly, the key features for predicting the RUL of aero engines were selected with the random forest algorithm and the maximal information coefficient. Based on this, the sliding window method was used to reconstruct engine operating data samples in the dataset. With the extracted key features as model input and RUL as output, a Stacking prediction model that integrated multiple individual machine learning algorithms was built. Compared with the model constructed by a single machine learning algorithm, the proposed Stacking model performed better. Compared with the optimal base learner, the RMSE and Score values of the Stacking model were reduced by 19.16% and 38.52%, respectively. The ablation experiment proved that feature screening could improve the accuracy of the Stacking model. It is proved that the Stacking multi-model fusion method with feature screening can effectively improve the prediction accuracy of RUL.

Key words

aero engine / useful life prediction / ensemble learning / Stacking model / multi-model fusion / feature selection

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BAI Weiwei, YANG Zhiyu, WANG Xiaomin, CHAI Jin. Remaining Useful Life Prediction Method of Aero Engines Based on Stacking Multi-model Fusion[J]. Equipment Environmental Engineering. 2026, 23(5): 53-63 https://doi.org/10.7643/ issn.1672-9242.2026.05.007

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Funding

Basic Research Fund for Directly Affiliated Universities in Inner Mongolia Autonomous Region (JY20220291?JY20250046); Inner Mongolia Autonomous Region Department of Education First-class Discipline Scientific Research Special Project (YLXKZX-NGD-024)