基于Volterra级数的非线性非定常气动力降阶模型

发展了一种基于Volterra级数的非线性非定常气动力降阶模型。着重探讨了基于CFD／CSD耦合计算的Volterra核辨识方法。CFD／CSD耦合计算采用了一种简单的动网格快速生成方法，气动网格与结构网格节点间的物理信息交换采用一种改进的CVT方法。通过与CFD／CSD直接计算的结果对比，表明非定常气动力Volterra级数模型是一种效率高、精度好、能描述非线性、便于使用的降阶模型，特别适用于预测结构做非定常运动下的非定常气动力。     

推进剂稳态燃速最优化辨识

考虑侵蚀燃烧对推进剂稳态燃速的影响,将推进剂稳态燃速模型参数辨识问题转化为非线性规划问题求解。采用Powell方法和并行遗传算法组成的混合优化方法,提高了非线性规划问题求解的效率和质量,得到了推进剂稳态燃速模型参数的全局最优辨识值。通过对设计空间的可视化进行优化收敛过程的参数分析,近似得到侵蚀燃烧模型参数的不确定性区间。     

挠性空间结构变形的自适应辨识

本文以空间控制中的挠性结构变形的辨识为背景,以李雅普诺夫稳定性理论为基础,从辨识的一致性原则出发,给出时变参数的自适应辨识算法。该算法具有梯度型递推形式,结构简单、容易实现。计算机模拟结果表明该算法是解决时变参数辨识的一种有效方法。     

Variable stiffness design of redundantly actuated planar rotational parallel mechanisms

Redundantly actuated planar rotational parallel mechanisms (RAPRPMs) adapt to the requirements of robots under different working conditions by changing the antagonistic internal force to tune their stiffness. The geometrical parameters of the mechanism impact the performances of modulating stiffness. Analytical expressions relating stiffness and geometrical parameters of the mechanism were formulated to obtain the necessary conditions of variable stiffness. A novel method of variable stiffness design was presented to optimize the geometrical parameters of the mechanism. The stiffness variation with the internal force was maximized. The dynamic change of stiffness with the dynamic location of the mechanism was minimized, and the robustness of stiff-ness during the motion of the mechanism was ensured. This new approach to variable stiffness design can enable off-line planning of the internal force to avoid the difficulties of on-line control of the internal force.     

Motion prediction of a non-cooperative space target

Capturing a non-cooperative space target is a tremendously challenging research topic. Effective acquisition of motion information of the space target is the premise to realize target capture. In this paper, motion prediction of a free-floating non-cooperative target in space is studied and a motion prediction algorithm is proposed. In order to predict the motion of the free-floating non-cooperative target, dynamic parameters of the target must be firstly identified (estimated), such as inertia, angular momentum and kinetic energy and so on; then the predicted motion of the target can be acquired by substituting these identified parameters into the Euler’s equations of the target. Accurate prediction needs precise identification. This paper presents an effective method to identify these dynamic parameters of a free-floating non-cooperative target. This method is based on two steps, (1) the rough estimation of the parameters is computed using the motion observation data to the target, and (2) the best estimation of the parameters is found by an optimization method. In the optimization problem, the objective function is based on the difference between the observed and the predicted motion, and the interior-point method (IPM) is chosen as the optimization algorithm, which starts at the rough estimate obtained in the first step and finds a global minimum to the objective function with the guidance of objective function’s gradient. So the speed of IPM searching for the global minimum is fast, and an accurate identification can be obtained in time. The numerical results show that the proposed motion prediction algorithm is able to predict the motion of the target.     

FUZZY IDENTIFICATION METHOD BASED ON A NEW OBJECTIVE FUNCTION

Many fuzzy models on modeling and controlmethods have been developed since Takagi-Sugeno model was proposed[1] .The main prob-lems of the fuzzy identifying method based on T-S model appear in the following two aspects:　　 1 It is important what heuristic knowledgeis chosen to acquire the premise structure of theT- S model.This problem is related to the opti-mal partition of input space of premise part andmodeling accuracy.　　 2 Itis crucial whatidentifying method is u-tilized to estimate …     

基于复杂网络的航空制造供应链关键节点识别研究

随着不稳定因素的增加以及航空制造供应链的参与主体增多，航空制造供应链的管理所面临的风险也随之增大。因此针对航空制造供应链网络的风险管理，以复杂网络为工具研究供应链网络中的关键节点识别问题，从而帮助航空供应链提升抗风险能力。通过分析我国航空制造供应链网络现状和特点，提出供应链形成机制并划分供应链层级，对航空制造供应链进行构建及指标界定，对度中心性、介数中心性、接近中心性三种经典中心性算法以及传统K-Shell 分解算法进行加权改进；结合熵值-TOPSIS 法提出一种针对加权网络的供应链关键节点识别算法——WKC 算法，通过构造网络来进行算例分析，验证该种算法的有效性。结果表明：本文提出的WKC 算法原理科学、计算复杂度较低，为航空制造等高端装备制造业供应链的风险管理提供了一定的参考。     

变截面悬臂梁结构动载荷辨识方法

在航空航天领域，作用在结构上动载荷的确定对结构健康监测是非常必要和重要的。为此，本文以类似机翼结构的变截面悬臂梁结构为研究对象，提出了一种基于光纤光栅传感器与卡尔曼滤波器的动载荷识别方法。首先，根据变截面梁单元形式，推导出变截面梁的质量矩阵与刚度矩阵，建立动力学运动方程。然后，以光纤光栅传感器测得的应变信息作为观测信号，通过卡尔曼滤波器生成的增益矩阵、新息序列矩阵以及协方差矩阵，得到灵敏度矩阵和估计力的增益矩阵。在此基础上，利用广义回归模型及其最小二乘算法，估算出动载荷大小、判断出动载荷激励位置。借助数值仿真与实验手段，分别验证了该方法对于单点正弦激励、方波激励、锯齿波激励以及多点同时激励等工况下的动载荷识别效果。结果表明，本文所提算法具有较好的动载荷识别效果和噪声抑制能力，能够为未来风洞试验和真实飞行试验环境中诸如大展弦比机翼表面气动压力等载荷实时辨识、气动外形自适应控制以及结构健康监测提供技术支撑。     

A novel none once per revolution blade tip timing based blade vibration parameters identification method

The vibration caused blade High Cycle Fatigue (HCF) is seriously affects the safety operation of turbomachinery especially for aero-engine. Thus, it is crucial important to identify the blade vibration parameters and then evaluate the dynamic stress amplitude. Blade Tip Timing (BTT) method is one of the promising method to solve these problems. While, it need a high resolution Once Per Revolution (OPR) signal which is difficult to get for the aero-engine. Here, a Coupled Vibration Analysis (CVA) method for identifying blade vibration parameters by a none OPR BTT is proposed. The method assumes that every real blade has its own vibration performance at a given speed. Whereby, it can take any blade as the reference blade, and the other blades using the reference blade as the OPR for vibration displacement calculating and further parameter identifying. The proposed method is validated by numerical model. Also, experimental studies are carried out on a straight blade and a twisted three dimensional blade test rig as well as a large industrial axial compressor respectively. The results show that the proposed method can accurately identify the blade synchronous vibration parameters and quantitatively evaluate the mistuning in bladed disks, which lays a foundation for the reliability improvement of aero-engine.     

Boundary condition modelling and identification for cantilever-like structures using natural frequencies

The actual boundary conditions of cantilever-like structures might be non-ideally clamped in engineering practice, and they can also vary with time due to damage or aging. Precise modelling of boundary conditions, in which both the boundary stiffness and the boundary mass should be modelled correctly, might be one of the most significant aspects in dynamic analysis and testing for such structures. However, only the boundary stiffness was considered in the most existing methods. In this paper, a boundary condition modelling and identification method for cantilever-like structures is proposed to precisely model both the boundary stiffness and the boundary mass using sensitivity analysis of natural frequencies. The boundary conditions of a cantilever-like structure can be parameterized by constant mass, constant rotational inertia,constant translational stiffness, and constant rotational stiffness. The relationship between natural frequencies and boundary parameters is deduced according to the vibration equation for the lateral vibration of a non-uniform beam. Then, an iterative identification formulation is established using the sensitivity analysis of natural frequencies with respect to the boundary parameters. The regularization technique is also used to solve the potential ill-posed problem in the identification procedure.Numerical simulations and experiments are performed to validate the feasibility and accuracy of the proposed method. Results show that the proposed method can be utilized to precisely model the boundary parameters of a cantilever-like structure.