Life Prediction of Carrier-Based Aircraft Replaceable Units With Time-Varying Drift and Optimization Strategy for Imperfect Maintenance

The aircraft is the sharpest sword of the carrier, and the lifetime of the replaceable units determines its availability. At present, few studies refer to the hybrid impact of maintenance and degradation on the lifetime. This article proposes a model for predicting the remaining useful life of the r...

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Veröffentlicht in:IEEE transactions on reliability 2024-06, Vol.73 (2), p.952-966
Hauptverfasser: Luan, Tiantian, Sun, Mingxiao, You, Bo, Yao, Hanhong, Fu, Qiang
Format: Artikel
Sprache:eng
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Zusammenfassung:The aircraft is the sharpest sword of the carrier, and the lifetime of the replaceable units determines its availability. At present, few studies refer to the hybrid impact of maintenance and degradation on the lifetime. This article proposes a model for predicting the remaining useful life of the replaceable units, which considers the combination of imperfect maintenance and nonlinear degradation. The problem of remaining useful life estimation of carrier-based aircraft replaceable units considering the degradation process with the time-varying nonlinear coefficient and condition-based maintenance has been studied. The composition and original data of the replaceable unit system have been analyzed. A condition-based maintenance with time-varying nonlinear model and decision model has been established considering assumptions and characteristics. The condition-based maintenance decision model is established by taking the total cost rate of the whole life process of the carrier-based aircraft replaceable unit as the decision target. Besides, the multidimensional search method is used to obtain the optimal condition-based maintenance threshold and maximum number of condition-based maintenance, to achieve the ultimate goal of reducing the maintenance cost of the carrier-based aircraft replaceable unit system. Finally, the simulation confirms that predictions of remaining useful life with the proposed model are more accurate than those with a linear model and a hybrid remaining useful life prediction method.
ISSN:0018-9529
1558-1721
DOI:10.1109/TR.2023.3328316