单部件加速退化系统的视情维修策略优化

doi:10.3969/j.issn.1001-506X.2020.03.015

Abstract

Abstract:

Optimization of condition-based maintenance strategy is studied for single-unit accelerated degrading systems, to minimize the average maintenance cost rate, by setting the optimal inspection interval and the near-to-failure threshold. To handle the sparse maintenance data, the grey model theory is used to establish the accelerated degrading model of the system, as it is suitable for small-sample modeling. Considering that there exist multiple correlations among the number of previous repairs, the degradation state and the maintenance duration, the partial least square is used to establish a multivariable regression model. Then, the objective function based on average maintenance cost rate is given, and the improved grey wolf optimization method solves the optimal decision variables. Finally, a numerical example is given to illustrate the feasibility of the proposed optimization method of condition-based maintenance strategy.

Key words: condition-based maintenance, strategy optimization, accelerated degrading system, grey model, partial least square, grey wolf optimization algorithm

CLC Number:

N945.17

Chuang CHEN, Ningyun LU, Bin JIANG, Yin XING. Optimization of condition-based maintenance strategy for single-unit accelerated degrading systems[J]. Systems Engineering and Electronics, 2020, 42(3): 613-619.

Figures/Tables 8

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Table 1

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References 28

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退化特性	T^*	M^*	CR
匀速	1.951	3.820	138.619
加速	1.495	3.866	159.343

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Optimization of condition-based maintenance strategy for single-unit accelerated degrading systems

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