Research On Fleet Maintenance Decision-making Based On Structure Fatigue Life Prediction

Equipment health management plays a crucial role in the modern production system,especially for aviation industry in where the manufacturing cost of the aircraft parts is very expensive as well as high structure reliability is required.Therefore,the performance of aircraft health management is an important indicator to evaluate the management level of aviation industry.As the core of health management theory,condition-based maintenance make maintenance plans according to the equipment health trends.These maintenance scheduling have integrated the advantages of high reliability,economy,and efficiency in ensuring the safety of fleet,reducing maintenance cost and downtimes,as well as improving aircraft availability and fleet availability.The condition-based maintenance strategies have important scientific significances for guiding avia tion administrative department to implement effective fleet health management.This paper studies the fleet health management,a remaining useful life prediction method for aircraft structure is proposed to support maintenance decision-making.The maintenance decision-making problem of multiple aircraft structures for an aircraft of a fleet is systematic studied.The main research content of this paper are as following:(1)A novel model fusion based remaining useful life prediction method is proposed to alleviate the negative influence on prediction accuracy caused by the uncertainty of incompletion of status information,as well as environmental noise.Firstly,a discrete state-space model is established based on the Paris law,then the nonlinear Kalman filtering is applied to estimate the two unknown in the discrete state-space model by combining with the real-time information obtained by sensors.The numerical experiments indicated that the proposed method overcomes the disadvantage of traditional damage tolerance method which is too conservative in predicting the remaining useful life,and highly improve the prediction accuracy.(2)To overcome the disadvantages of traditional static maintenance decision-making strategies for multiple aircraft structures,which c annot take the real time status data into maintenance decision-making and the arranged maintenance plan cannot dynamic adjust to adapt the complex and changeable working condition,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.Moreover,in terms of the harsh and changing working condition,a dynamic grouping optimization method is further proposed based on the rolling-horizon model.The numerical experiments indicated that the proposed method can minimize the affects caused by the uncertainty of structure damage,as well as reduce the maintenance cost and downtimes.(3)A collaborative optimization based two-level dynamic maintenance decision-making structure is established through systematic analyzing the independence of structure degradation.Furthermore,a collaborative optimization based fleet dynamic maintenance decision-making model constrained by maintenance hangers and aimed to optimize the fleet maintenance cost,maintenance resource utilization as well as the fleet availability simultaneously is proposed.The proposed model is divided into two level: system level and sub-system level to reduce the computational complexity,as well as to overcome the difficulties caused by multiple variables.Last but not least,the proposed model avoids the disadvantages of the tradition fleet maintenance decision-making model which concentrated on single optimization object and ignored the importance of optimizing maintenance resource utilization.(4)A fleet maintenance decision-making optimization method based on collaborative optimization is proposed to solve the above-mentioned fleet maintenance decision-making model.A variable selection strategy is applied to avoid the disadvantages of computational complexity and no convergence broug ht by too many optimization variables.Moreover,a cooperative optimization strategy between system level and sub-system level is applied to help balance the dynamic grouping optimization result of sub-system level and fleet maintenance decision-making requirements of system level,as well as to optimize the fleet maintenance cost,maintenance resource utilization and the fleet availability simultaneously.The numerical experiments illustrated that the maintenance plan obtained by the proposed method can be dynamic updated to meet the actually maintenance requirements,the maintenance cost is reduced and the maintenance resource utilization and fleet availability is efficiently improved.In light of the above research,a PHM-based aircraft structure health management system is developed to help the fleet health management becoming more integrated,digital and informational.The system integrates the process of data acquisition(real-time status information of aircraft),data processing(reliability assessment of aircraft structures)as well as maintenance decision-making.It improves the economic performance of aviation equipment management and the maintenance support capacity.