飞机多疲劳结构动态成组维修决策优化方法
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摘要
以多个疲劳结构组成的飞机为对象,针对此类系统存在的维护困难、停机成本大等特点,研究多疲劳结构动态成组维修优化问题.在充分考虑结构停机维修用时以及多个疲劳结构之间维修相关性对于飞机使用率和维修费用的影响下,以维修费用和使用率为优化目标,以可靠度为约束,建立多疲劳结构动态成组维修决策优化模型.考虑飞机工作环境的严酷性和动态性,基于滚动时间轴模型,提出多疲劳结构动态成组维修决策优化方法.为了充分利用传感器获得的实时状态信息降低结构服役过程中损伤不确定性对维修计划制定的影响,并使维修计划能够适应复杂多变的动态环境,当每执行完一次停机维修活动或出现新的结构状态信息时,通过将维修决策时间窗口进行不断的滚动,使维修计划能够自适应地动态调整,达到无限规划周期的效果.
This paper focuses on handling dynamic grouping maintenance planning problem for the aircraft with multiple fatigue structures, which has been widely studied due to expensive replacement of machinery as well as the high costs of downtime. A dynamic grouping maintenance planning optimization model concentrated on both minimizing the maintenance cost and maximizing the availability of the aircraft and constrained by the maintenance resource is established for the multiple fatigue structures through taking into consideration of the economic dependence among the structures. Then, in terms of the harsh and changing working condition, a dynamic grouping optimization method is further proposed based on the rolling-horizon model. The maintenance decision horizon is rolled and the maintenance plan is self-adaptive when new real-time status is available or the maintenance plan is executed, in order to minimize the affects caused by the uncertainty of structure damage.
This paper focuses on handling dynamic grouping maintenance planning problem for the aircraft with multiple fatigue structures, which has been widely studied due to expensive replacement of machinery as well as the high costs of downtime. A dynamic grouping maintenance planning optimization model concentrated on both minimizing the maintenance cost and maximizing the availability of the aircraft and constrained by the maintenance resource is established for the multiple fatigue structures through taking into consideration of the economic dependence among the structures. Then, in terms of the harsh and changing working condition, a dynamic grouping optimization method is further proposed based on the rolling-horizon model. The maintenance decision horizon is rolled and the maintenance plan is self-adaptive when new real-time status is available or the maintenance plan is executed, in order to minimize the affects caused by the uncertainty of structure damage.
引文
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[9]白芳.民航发动机机群调度优化与视情维修决策方法研究[D].南京:南京航空航天大学民航学院,2009:71-93.(Bai F.Methods of scheduling and condition based maintenance decision making in civil aero engine fleet[D].Nanjing:College of Civil Aviation,Nanjing University of Aeronautics and Astronautics,2009:71-93.)
[10]蔡景,李鑫,肖罗椿.民用飞机成组维修方案优化模型研究[J].南京理工大学学报,2015,39(3):306-311.(Cai J,Li X,Xiao L C.Optimization model of group maintenance scheme for civil aircraft[J].J of Nanjing University of Science and Technology,2015,39(3):306-311.)
[11]Feng Q,Bi X,Zhao X J,et al.Heuristic hybrid game approach for fleet condition-based maintenance planning[J].Reliability Engineering&System Safety2017,157:166-176.
[12]Wildeman R E,Dekker R,Smit A C J M.A dynamic policy for grouping maintenance activities[J].European J of Operational Research,1997,99(3):530-551.
[13]Hai C V,Do P,Barros A,et al.Maintenance grouping strategy for multi-component systems with dynamic contexts[J].Reliability Engineering&System Safety2014,132(132):233-249.
[14]Do P,Hai C V,Barros A,et al.Maintenance grouping for multi-component systems with availability constraints and limited maintenance teams[J].Reliability Engineering&System Safety,2015,142:56-67.
[15]Aizpurua J I,Catterson V M,Papadopoulos Y,et al Supporting group maintenance through prognosticsenhanced dynamic dependability prediction[J]Reliability Engineering&System Safety,2017,168:171-188.
[16]Barron Y.Group maintenance policies for an R-out-of-Nsystem with phase-type distribution[J].Annals of Operations Research,2018,261(1/2):79-105.
[17]Tian Z,Liao H.Condition based maintenance optimization for multi-component systems using proportional hazards model[J].Reliability Engineering&System Safety,2011,96(5):581-589.
[18]孙强,岳继光.基于不确定性的故障预测方法综述[J]控制与决策,2014,29(5):769-778.(Sun Q,Yue J G.Review on fault prognostic methods based on uncertainty[J].Control and Decision,201429(5):769-778.)
[19]Noortwijk J M V.A survey of the application of gamma processes in maintenance[J].Reliability Engineering&System Safety,2009,94(1):2-21.
[2]Zhang M,Ye Z,Xie M.A condition-based maintenance strategy for heterogeneous populations[J].Computers&Industrial Engineering,2014,77:103-114.
[3]宋恩鹏,陆华,何刚,等.多轴疲劳寿命分析方法在飞机结构上的应用[J].北京航空航天大学学报,201642(5):906-911.(Song E P,Lu H,He G,et al.Application of multi-axial fatigue life estimation methods to aircraft structural components[J].J of Beijing University of Aeronautics and Astronautics,2016,42(5):906-911.)
[4]Park C,Peters K.Optimization of embedded sensor placement for structural health monitoring of composite airframes[J].AIAA J,2012,50(11):2536-2545.
[5]Lin L,Luo B,Zhong S S.Development and application of maintenance decision-making support system for aircraft fleet[J].Advances in Engineering Software,2017114(C):192-207.
[6]Xia T B,Xi L F,Lee J,et al.Condition-base maintenance for intelligent effects and environmental condition[J].Int J of Production Research,2013,51(15):4585-4596.
[7]甘婕,曾建潮.考虑劣化状态的单机调度与维修决策集成模型[J].控制与决策,2016,31(3):513-520.(Gan J,Zeng J C.Integrated model of single-machine scheduling and maintenance decision for degrading state systems[J].Control and Decision,2016,31(3):513-520.)
[8]李大伟,张志华,钟强晖,等.复杂退化系统的组合维修策略优化[J].航空学报,2015,36(3):872-880.(Li D W,Zhang Z H,Zhong Q H,et al.Optimal combination maintenance strategy of deteriorating complex system[J].Acta Aeronauticaet Astronautica Sinica,2015,36(3):872-880.)
[9]白芳.民航发动机机群调度优化与视情维修决策方法研究[D].南京:南京航空航天大学民航学院,2009:71-93.(Bai F.Methods of scheduling and condition based maintenance decision making in civil aero engine fleet[D].Nanjing:College of Civil Aviation,Nanjing University of Aeronautics and Astronautics,2009:71-93.)
[10]蔡景,李鑫,肖罗椿.民用飞机成组维修方案优化模型研究[J].南京理工大学学报,2015,39(3):306-311.(Cai J,Li X,Xiao L C.Optimization model of group maintenance scheme for civil aircraft[J].J of Nanjing University of Science and Technology,2015,39(3):306-311.)
[11]Feng Q,Bi X,Zhao X J,et al.Heuristic hybrid game approach for fleet condition-based maintenance planning[J].Reliability Engineering&System Safety2017,157:166-176.
[12]Wildeman R E,Dekker R,Smit A C J M.A dynamic policy for grouping maintenance activities[J].European J of Operational Research,1997,99(3):530-551.
[13]Hai C V,Do P,Barros A,et al.Maintenance grouping strategy for multi-component systems with dynamic contexts[J].Reliability Engineering&System Safety2014,132(132):233-249.
[14]Do P,Hai C V,Barros A,et al.Maintenance grouping for multi-component systems with availability constraints and limited maintenance teams[J].Reliability Engineering&System Safety,2015,142:56-67.
[15]Aizpurua J I,Catterson V M,Papadopoulos Y,et al Supporting group maintenance through prognosticsenhanced dynamic dependability prediction[J]Reliability Engineering&System Safety,2017,168:171-188.
[16]Barron Y.Group maintenance policies for an R-out-of-Nsystem with phase-type distribution[J].Annals of Operations Research,2018,261(1/2):79-105.
[17]Tian Z,Liao H.Condition based maintenance optimization for multi-component systems using proportional hazards model[J].Reliability Engineering&System Safety,2011,96(5):581-589.
[18]孙强,岳继光.基于不确定性的故障预测方法综述[J]控制与决策,2014,29(5):769-778.(Sun Q,Yue J G.Review on fault prognostic methods based on uncertainty[J].Control and Decision,201429(5):769-778.)
[19]Noortwijk J M V.A survey of the application of gamma processes in maintenance[J].Reliability Engineering&System Safety,2009,94(1):2-21.