| Citation: | WANG K，GUO Y Q，ZHAO W L，et al. Remaining useful life prediction of aeroengine based on SSAE and similarity matching[J]. Journal of Beijing University of Aeronautics and Astronautics，2023，49（10）：2817-2825 （in Chinese） doi: 10.13700/j.bh.1001-5965.2021.0741
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As a highly complex thermal machinery, the prognosis of the remaining useful life (RUL) of an aero-engine is often used as an important guarantee to improve safety and economy. In order to increase the engine’s remaining usable life prediction accuracy, a strategy based on stacked sparse autoencoders (SSAE) and similarity matching is proposed in this study. Firstly, Spearman’s rank correlation coefficient (SRCC) is utilized as a fitness function and optimizes the candidate set of fusion parameters through a genetic algorithm (GA). The SSAE fuses the optimal parameter set in order to generate the feature comprehensive index. The results of the life prediction are then obtained by using the similarity matching approach to search the history database worldwide for the best matching trajectory. Finally, the C-MAPSS dataset published by the National Aeronautics and Space Administration (NASA) is obtained to verify the validity of the fusion index and method.
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