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A Hybrid Degradation Evaluation Model for Aero-Engines

Likun Ren, Haiqin Qin, Na Cai, Bianjiang Li and Zhenbo Xie ()
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Likun Ren: Qingdao Campus, Naval Aviation University, Qingdao 266041, China
Haiqin Qin: Qingdao Campus, Naval Aviation University, Qingdao 266041, China
Na Cai: Qingdao Campus, Naval Aviation University, Qingdao 266041, China
Bianjiang Li: Qingdao Campus, Naval Aviation University, Qingdao 266041, China
Zhenbo Xie: Qingdao Campus, Naval Aviation University, Qingdao 266041, China

Sustainability, 2022, vol. 15, issue 1, 1-18

Abstract: The non-convergence and low efficiency of the thermodynamic model make them difficult to be used in the aero-engines degradation evaluation, while the negligence of the thermodynamics process of data-driven degradation evaluation methods makes them inaccurate and hard to analyze the actual degradation of air path components. So, we propose a thermodynamic-based and data-driven hybrid model for aero-engine degradation evaluation. Different from thermodynamic-based methods, the iteration calculation is converted to the forward flow in the proposed neural network, thus improving convergence. Moreover, a multi-objective loss function considering the components co-operation process and fusion training process fully taking advantage of simulation and degradation trajectory datasets are proposed to improve the degradation evaluation accuracy. The test case is carried out on NASA’s benchmark for aero-engine degradation evaluation. The result shows that the proposed method can improve the accuracy significantly, which suggests its effectiveness.

Keywords: remaining useful life; hybrid model; aero-engine; degradation evaluation (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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