A cost driven predictive maintenance policy for structural airframe maintenance

Airframe maintenance is traditionally performed at scheduled maintenance stops.The decision to repair a fuselage panel is based on a fixed crack size threshold,which allows to ensure the aircraft safety until the next scheduled maintenance stop.With progress in sensor technology and data processing techniques,structural health monitoring (SHM) systems are increasingly being considered in the aviation industry.SHM systems track the aircraft health state continuously,lead ing to the possibility of planning maintenance based on an actual state of aircraft rather than on a fixed schedule.This paper builds upon a model-based prognostics framework that the authors developed in their previous work,which couples the Extended Kalman filter (EKF) with a first order perturbation (FOP) method.By using the information given by this prognostics method,a novel cost driven predictive maintenance (CDPM) policy is proposed,which ensures the aircraft safety while minimizing the maintenance cost.The proposed policy is formally derived based on the trade-off between probabilities of occurrence of scheduled and unscheduled maintenance.A numerical case study simulating the maintenance process of an entire fleet of aircrafts is imple mented.Under the condition of assuring the same safety level,the CDPM is compared in terms of cost with two other maintenance policies:scheduled maintenance and threshold based SHM maintenance.The comparison results show CDPM could lead to significant cost savings.     

Real-time object tracking via least squares transformation in spatial and Fourier domains for unmanned aerial vehicles

This paper addresses the problem of real-time object tracking for unmanned aerial vehicles. We consider the task of object tracking as a classification problem. Training a good classifier always needs a huge number of samples, which is always time-consuming and not suitable for realtime applications. In this paper, we transform the large-scale least-squares problem in the spatial domain to a series of small-scale least-squares problems with constraints in the Fourier domain using the correlation filter technique. Then, this problem is efficiently solved by two stages. In the first stage, a fast method based on recursive least squares is used to solve the correlation filter problem without constraints in the Fourier domain. In the second stage, a weight matrix is constructed to prune the solution attained in the first stage to approach the constraints in the spatial domain. Then, the pruned classifier is used for tracking. To evaluate proposed tracker's performance, comprehensive experiments are conducted on challenging aerial sequences in the UAV123 dataset. Experimental results demonstrate that proposed approach achieves a state-ofthe-art tracking performance in aerial sequences and operates at a mean speed of beyond 40 frames/s. For further analysis of proposed tracker's robustness, extensive experiments are also performed on recent benchmarks OTB50, OTB100, and VOT2016.     

A regional tropospheric model for airborne GPS applications

A regional tropospheric model can be constructed using surveys from GPS ground networks. Using this model the tropospheric delays of a kinematic station within the region can be interpolated. However, such a model is generally not suitable for an airborne platform high above the ground networks. In this paper, a method of constructing a regional tropospheric model for airborne GPS applications is described. First, the kinematic station in the air is projected onto the ground. Then the tropospheric delays at projected point are interpolated from those of the ground networks. Finally, the tropospheric delays at projected point are extended upward to the airborne platform using pressure and temperature gradients and humidity exponential function. For validation of this method, the data of airborne campaign carried out by BKG in cooperation with GFZ and BGR 2008 in the northern Alps are used. The results show that GPS kinematic positioning precision in height component can be improved using this method.     

Simultaneous state and actuator fault estimation for satellite attitude control systems

In this paper, a new nonlinear augmented observer is proposed and applied to satellite attitude control systems. The observer can estimate system state and actuator fault simultaneously. It can enhance the performances of rapidly-varying faults estimation. Only original system matrices are adopted in the parameter design. The considered faults can be unbounded, and the proposed augmented observer can estimate a large class of faults. Systems without disturbances and the fault whose finite times derivatives are zero piecewise are initially considered, followed by a discussion of a general situation where the system is subject to disturbances and the finite times derivatives of the faults are not null but bounded. For the considered nonlinear system, convergence conditions of the observer are provided and the stability analysis is performed using Lyapunov direct method. Then a feasible algorithm is explored to compute the observer parameters using linear matrix inequalities (LMIs). Finally, the effectiveness of the proposed approach is illustrated by considering an example of a closed-loop satellite attitude control system. The simulation results show satisfactory perfor-mance in estimating states and actuator faults. It also shows that multiple faults can be estimated successfully.     

基于动态逆-滑模的高速飞行器控制器设计

吸气式高超声速飞行器巡航状态下飞行环境复杂,建模时存在非线性以及参数摄动.基于小扰动假设的传统经典控制理论难以适应当前任务对鲁棒性的要求,对此提出了一种非线性动态逆-滑模控制律改进方法.通过对吸气式高超声速飞行器模型精确反馈线性化得到解耦形式的线性方程,为速度和高度设计出动态逆控制律来抵消非线性特性,在动态逆的基础上采用滑模变结构来补偿参数摄动带来的误差.仿真结果表明,所设计的控制方法具有良好的动态性能及鲁棒性.     

基于Kalman滤波的变体飞行器T-S模糊控制

针对变体飞行器的跟踪控制问题,提出了一种基于Kalman滤波的T-S模糊控制方法。考虑飞行器系统状态不可测,引入惯导数据作为辅助信息,利用Kalman滤波算法融合飞控信息与惯导信息实现状态估计。由于变体飞行器在不同变形结构下气动特性变化较大,为便于控制器设计,采用小扰动线性化方法得到飞行器在不同平衡点处的局部线性模型,并通过状态反馈方法设计局部控制器,局部线性模型和局部控制器通过模糊集和模糊规则聚合成一个连续光滑的全局T-S模糊模型和T-S模糊控制器。通过综合Kalman滤波器与T-S模糊控制器得到一个基于Kalman滤波的T-S模糊控制器。仿真结果表明,该控制器在变形过程中能够实现状态估计,保证飞机的跟踪性能。     

带非线性支撑的转子有限元模型求解方法

用数值方法研究了非线性支撑的柔性转子系统的动学行为,提出了一种将有限元与非线性支撑结合的模型和求解方法。利用有限元法(FEM)构建转轴和转盘部分的模型,通过矩阵进行组合;利用离散元方法对包含滚动轴承和挤压油膜阻尼器(SFD)的支撑部分进行建模,此部分包含4个单元,分别为轴承内圈、外圈、SFD内圈和支撑鼠笼。有限元部分和离散元部分通过轴端节点相连,仿真过程中轴端位移传递给非线性支撑部分,支撑部分通过位移计算得到的非线性力反过来作用于有限元转子轴端部分。为了耦合求解有限元转子和非线性支撑组成的数学模型,提出了一种综合的迭代求解方法,克服传统的有限元求解方法对轴端隐性非线性支撑的求解局限性。由于转轴部分采用了Timoshenko梁单元建模,对比与简单转子模型,可以考虑陀螺力矩和轴的柔性特征,更能体现非线性支撑对振动真实影响。在建立的20个轴单元的有限元转子模型中,非线性响应更多体现在靠近非线性支撑的节点1和节点21处,响应频谱中靠近轴端的节点能体现出滚动轴承的2倍和3倍变柔振动频率。     

瞬变流速作用下姿控发动机燃料管路的非线性振动特性分析

为研究瞬变流速激励下某型卫星姿控发动机燃料输送管路的非线性振动特性,采用加权余量法和四阶Runge—Kutta法对燃料输送管路的非线性液固耦合振动模型进行了数值仿真,研究不同燃料流速下、电磁阀开关时长对燃料管路非线性振动稳定性的影响.仿真结果表明,依据管路特征线可将管路振动分为稳定振动区和不稳定振动区,且不稳定振动主要...