考虑多种故障模式和多阶段故障过程的装备预防性维修策略优化模型

doi:10.12305/j.issn.1001-506X.2026.03.17

Abstract

Abstract:

A reliability model for single-component equipment systems is constructed to address the complex fault processes of weapon equipment under natural damage and various external shocks in the current high-intensity training environment, taking into account multiple fault modes and multi-stage fault processes. A detection-based preventive maintenance strategy is adopted, which involves regularly inspecting equipment to identify and replace components with potential faults. Based on equipment reliability analysis and replacement reward theory, explicit expressions for expected availability and expected cost rate are derived, and an equipment utilization efficiency model is subsequently constructed. By combining data analysis and optimization algorithms, the optimal detection interval for equipment utilization efficiency is determined. Finally, the proposed model and optimization method are validated through examples to effectively improve the operational efficiency of equipment compared to traditional models. This can provide some reference for fault prediction and preventive maintenance strategy optimization of current weapon equipment.

Key words: preventive maintenance, external shock, competing failure, random environment, reliability mode

CLC Number:

Shihan TAN, Quan SHI, Qiwei HU, Yongsheng BAI, Dunxiang ZHU, Fang ZHANG, Peng KE. Preventive maintenance policy optimization model of equipment considering multiple failure modes and multi-stage failure process[J]. Systems Engineering and Electronics, 2026, 48(3): 908-917.

Figures/Tables 12

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References 19

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参数	取值	参数	取值
$ {v}_{X},{v}_{Y} $	0.05，0.10	$ {T}_{i},{T}_{p},{T}_{f} $	1，4，10
$ {\varphi }_{X},{\varphi }_{Y} $	0.01，0.02	$ {C}_{i},{C}_{p},{C}_{f},{C}_{n} $	5，20，80，1
$ {\gamma }_{X},{\gamma }_{Y} $	$ 5\times {10}^{-4},1\times {10}^{-3} $	$ {{\mathrm{EA}}}_{\min } $	0.88
$ {\mu }_{X},{\mu }_{Y} $	0.005，0.01	$ {{\mathrm{EC}}}_{\max } $	0.93
$ {\sigma }_{X}{}^{2},{\sigma }_{Y}{}^{2} $	$ {0.001}^{2},{0.001}^{2} $	$ {T}_{\max } $	60

$ {a}_{1},{a}_{2} $	$ {T}^{\ast } $	$ Z\left({T}^{\ast }\right) $	$ {\mathrm{EA}}\left({T}^{\ast }\right) $	$ {\mathrm{EC}}\left({T}^{\ast }\right) $
1, 0	31	0.895 5	0.895 5	0.766 5
0, −1	22	0.736 7	0.892 3	0.736 7
1, −1	23	0.155 9	0.893 1	0.737 2
1, −4	22	−2.054 4	0.892 3	0.736 7
4, −1	24	2.836 3	0.893 7	0.738 7
1, −8	22	−5.001 0	0.892 3	0.736 7
8, −1	26	6.413 5	0.894 7	0.744 0

模型	场景1		场景2
模型	$ {T}^{\ast } $	$ {\mathrm{EA}}\left({T}^{\ast }\right) $	$ {T}^{\ast } $	$ {\mathrm{EC}}\left({T}^{\ast }\right) $
A	31	0.895 5	22	0.736 7
B	32	0.895 4	24	0.738 7
C	40	0.892 2	31	0.766 5
D	42	0.893 2	33	0.777 8

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Preventive maintenance policy optimization model of equipment considering multiple failure modes and multi-stage failure process

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