基于非线性阻尼的航空发动机高压转子拉杆结构装配检测方法

 为了提高航空发动机高压转子拉杆结构的装配质量,提出了基于非线性阻尼的装配检测方法。该方法运用组合阻尼模型描述拉杆结构的非线性接触特性,并通过能量方程推导出基于Hilbert-Huang变换(HHT)方法的非线性阻尼的识别公式。在拉杆结构正常装配、单个螺栓松动和2个不相邻螺栓松动的3种情况下,采用非线性阻尼识别法进行实验,将3种情况得到的实验结果进行对比,发现基于组合阻尼模型得到的非线性阻尼与装配情况具有强烈的相关性,从而验证了基于非线性阻尼的装配检测方法的有效性。     

Adaptive Control of a Flexible Beam Using Least Square Lattice Filters

An indirect adaptive control scheme for the control of flexible structures using least square lattice filters for on-line identification of the number of modes, mode shapes, and modal amplitudes is presented. The control law is based on modal pole placement. The system requires on-line validation of the results of the identification scheme before allowing changes in control law parameters. Successful adaptive control is demonstrated using the simulations for the 12 ft free-free beam apparatus at NASA Langley Research Center.     

RBF网络用于边界层转捩中抽吸流优化控制

 在抽吸气流控制边界层转捩问题中 ,将径向基神经网络用于抽吸流速与转捩位置间的函数关系建模 ,构造了网络结构 ,利用一组两通道抽吸流控制转捩的实验数据训练网络 ,获得了优化的网络参数。在此基础上 ,利用训练网络所获得的输入 /输出关系模型求解了最优抽吸流速。结果表明 ,RBF网络可有效地应用于边界层转捩主动控制中的系统函数关系建模。     

基于随机子空间方法的模态参数识别研究

随机子空间识别 (StochasticSubspaceIdentification ,以下简称SSI)方法是一种新的时域识别方法 ,该方法仅用自然响应数据 ,通过QR分解和SVD分解等一套正交投影算法识别系统模型。研究了SSI方法在模态参数识别领域的应用。采用NASAmini mast模型 ,仿真分析了SSI算法控制参数选择技巧 ,论证了其参数识别精度。通过处理日本CFT大楼实测数据 ,研究了SSI方法识别真实结构模态参数的问题。应用Kalman滤波器 ,测量响应可以分解为模态空间响应 ,将信号功率谱分解成多条单自由度系统功率谱。     

Numerical Simulation of Rotor Flow Field Based on Overset Grids and Several Spatial and Temporal Discretization Schemes

A numerical method based on solutions of Euler/Navier-Stokes (N-S) equations is developed for calculating the flow field over a rotor in hover. Jameson central scheme, van Leer flux-vector splitting scheme, advection upwind splitting method (AUSM) scheme, upwind AUSM/van Leer scheme, AUSM+ scheme and AUSMDV scheme are implemented for spatial discretization, and van Albada limiter is also applied. For temporal discretization, both explicit Runge-Kutta method and implicit lower-upper symmetric Gauss-Seidel (LU-SGS) method are attempted. Simultaneously, overset grid technique is adopted. In detail, hole-map method is utilized to identify intergrid boundary points (IGBPs). Furthermore, aimed at identification issue of donor elements, inverse-map method is implemented. Eventually, blade surface pressure distributions derived from numerical simulation are validated compared with experimental data, showing that all the schemes mentioned above have the capability to predict the rotor flow field accurately. At the same time, vorticity contours are illustrated for analysis, and other characteristics are also analyzed.     

一种基于响应信息的整体叶盘结构失谐识别方法

以谐调叶盘有限元模型解析模态和真实失谐结构的稳态响应作为基础信息,提出一种整体叶盘结构失谐识别方法。该方法基于公称模态子集（SNM）降阶技术,降低了识别过程的计算花费以及对基础信息量的要求;采用子矩阵型技术使得失谐参数定义更加自由,并使得该方法具有模型修正的功能;直接利用实测的稳态响应数据作为输入参数,并且不需要施加在结构上的外力信息,提高了基础数据可靠性并有效降低了实际测量的难度。最后以一个整体叶盘结构的仿真分析证明了该方法的有效性。     

跨声速风洞颤振试验模型激振与数据处理方法研究

简述了几种主要激励方法在颤振实验中的优缺点,分别用瞬态激励、有限带宽白噪声激励和单频激励进行地面模态实验,测量机翼模型的振动响应,并用STD、ARMA和复指数模态参数识别等时域方法识别固有频率和模态阻尼,通过与软件计算结果对比分析得知,实测的固有频率与计算结果吻合很好。     

A Functionally Redundant Altimeter

A scheme to provide redundant sensor data in an automatic control system using the principle of functional redundancy is described. Normally there are three redundant radar altimeters used in the terminal phase of automatic landing of jet transport airplanes. This scheme replaces one of these altimeters with a data processing scheme based on a Kalman filter. The filter is driven by altitude rate and acceleration signals from the air data computer and vertical accelerometer. A special initialization technique employs the two altimeter signals. The feasibility of this scheme is indicated by tests in which data obtained from these several sensors during flight tests are used to drive the functionally redundant altimeter.     

Excitation control of a synchronous generator using a lookup table

A scheme involving the use of a lookup table is developed for the excitation control of a synchronous generator. The proposed control scheme, generator speed deviation, and acceleration deviation are taken as the input signals. These input signals are sampled and converted to linguistic terms before they are fed into the controller. The controller generates the desired output (control) signal by using a set of production rules (if-then rules) that are based on previous experience to relate the input signals to the output. The output signal is converted from linguistic terms to a numerical value before it is sent to the excitation system of the synchronous machine. To demonstrate the effectiveness of the proposed control scheme, digital simulations of a synchronous generator subject to a three-phase fault under different operating conditions were performed. It was found that the controller can improve the dynamic performance of a synchronous generator over a wide range of operating conditions. Since the controller does not require model identification, it is computationally efficient and is suitable for online excitation control, using a microcomputer     

航空发动机神经网络自适应控制研究

本文研究神经网络自适应控制方法及其在航空发动机控制中应用。结合某型航空涡喷发动机,首先研究采用神经网络进行非线性动态系统辨识,包括神经网络模型辨识的格式、输入信号形式等问题。然后,提出了一种神经网络自适应控制方法,阐明了该方法基本结构、原理。最后,在选定的设计点处进行发动机控制系统设计,当偏离设计点时,利用神经网络很强的学习、适应能力,通过在线修正神经网络参数,使控制系统仍保持良好性能。      

Implementing Aircraft Identification Schemes by Public Key Cryptosystems

The use of public key cryptosystems for identification purposes has already been suggested. The practical aspects of using such systems for aircraft identification are discussed. It is shown that the digital signature property is not mandatory for implementing an identification procedure. It is then shown how public key distribution systems can be used for identification purposes. The technical difficulties in implementing an identification scheme are finally discussed with possible solutions offered.     

一种识别单盘柔性转子不平衡的新方法

基于柔性转子瞬态响应和反向传播神经网络理论,提出了一种识别单盘柔性转子不平衡的新方法.通过转子的理论模型建立识别转子不平衡方位角的BP神经网络,在此基础上只需两次加速启动过程就可完成对转子不平衡的识别.首先通过BP神经网络和第一次启动过程的瞬态响应数据,识别出转子不平衡的方位角;然后再通过一次加试重启动过程,利用瞬态挠度的幅值与不平衡大小之间的线性关系,识别出不平衡的大小.实验结果证明了该方法的有效性.      

数据挖掘技术在飞行试验数据分析和气动参数辨识中的应用研究

为了检验飞行试验辨识结果的可信度,首次将数据挖掘技术用于飞行试验数据的分析和气动参数辨识,初步解决了试验数据有限、数据信息含量差别较大给聚类、分类、回归等分析处理带来的问题;提出了利用不同时间段、不同飞行批次的飞行数据在划分区间的气动特性分布来检验辨识结果可信度的方法;以某飞行器为对象,利用数据挖掘技术,建立了基于飞行试验数据的气动力数学模型,检验了辨识结果的一致性和可信度,并与地面试验结果进行了比较分析,给出了地面试验预测误差。多批次飞行试验数据的整体辨识结果表明,所发展的方法是可行和有效的。该项研究为验证辨识结果的可信度、建立基于飞行试验数据的气动模型提供了新的途径,并可应用于CFD 和风洞试验的验证与确认。     

一种基于遗传算法的动力学系统辨识方法

把遗传算法与最大似然法相结合，形成了一种基于遗传算法的动力学系统辨识方法，并以某轴对称战术导弹的非线性气动力参数仿真辨识为例，利用仿真技术，检验了该方法的实用性和有效性。结果表明，该方法是十分有效的。     

Identification method for helicopter flight dynamics modeling with rotor degrees of freedom

A comprehensive method based on system identification theory for helicopter flight dynamics modeling with rotor degrees of freedom is developed. A fully parameterized rotor flapping equation for identification purpose is derived without using any theoretical model, so the confidence of the identified model is increased, and then the 6 degrees of freedom rigid body model is extended to 9 degrees of freedom high-order model. Bode sensitivity function is derived to increase the accuracy of frequency spectra calculation which influences the accuracy of model parameter identification. Then a frequency domain identification algorithm is established. Acceleration technique is developed furthermore to increase calculation efficiency, and the total identification time is reduced by more than 50% using this technique. A comprehensive two-step method is established for helicopter high-order flight dynamics model identification which increases the numerical stability of model identification compared with single step algorithm. Application of the developed method to identify the flight dynamics model of BO 105 helicopter based on flight test data is implemented. A comparative study between the high-order model and rigid body model is performed at last. The results show that the developed method can be used for helicopter high-order flight dynamics model identification with high accuracy as well as efficiency, and the advantage of identified high-order model is very obvious compared with low-order model.     

系统识别与飞机颤振

本文在简要综述了系统识别技术在飞机颤振研究中的应用后,介绍了三种系统识别方法。重点讨论了其算法要点及理论基础。对有关数据处理问题也作了适当说明。基于复模态分析和优化技术的传递函数法可以精确识别出全部模态参数,并在带外挂机翼颤振模型试验中获得成功,该法可推广到仅有响应数据的风洞与飞行试验情况。脉冲响应和自回归滑动平均模型法采用了相关和最小二乘技术,可以在较强干扰情况下得到精确结果,后者还可求出估计值与真值的协方差。两种时域方法皆可无需专用信号分析设备而直接利用测量采样数据进行系统识别。     

一种基于短时机动试飞数据的动力学辨识优化方法

飞行动力学辨识算法的一个关键问题是,如何通过简单的机动获取所关心频率范围的响应特性。短时倍脉冲是一种易于实施的激励信号,兼顾试飞安全性与经济性,但与频域辨识法通常使用的扫频输入激励相比,短时机动频谱范围窄、信噪比低,一般难以得到准确的辨识结果。对如何基于短时机动飞行试验数据,提高辨识结果准确性的问题进行了研究。首先分析了经典Welch谱估计进行时域-频域转换过程中,影响非参数模型辨识精度的主要因素,提出了削减窗函数边缘缩减效应的数据预处理方法,并结合多窗口综合技术,提高频域特性辨识结果的精度。在参数化模型辨识过程中,针对有限频谱范围,提出了利用相干函数和功率谱密度加权综合,确定等效拟配的频率范围和频率节点的自适应方法,使得低阶等效拟配与输入激励信号高度相关,提高参数化模型辨识的精度、一致性和适应性。通过不同类型飞机的大量短时机动和少量扫频飞行试验数据模型辨识的工程应用示例,验证了动力学辨识优化方法算法稳定、结果准确,可满足飞行品质模态特性评价等应用需求。     

Identification of reduced-order model for an aeroelastic system from flutter test data

Recently, flutter active control using linear parameter varying (LPV) framework has attracted a lot of attention. LPV control synthesis usually generates controllers that are at least of the same order as the aeroelastic models. Therefore, the reduced-order model is required by syn-thesis for avoidance of large computation cost and high-order controller. This paper proposes a new procedure for generation of accurate reduced-order linear time-invariant (LTI) models by using sys-tem identification from flutter testing data. The proposed approach is in two steps. The well-known poly-reference least squares complex frequency (p-LSCF) algorithm is firstly employed for modal parameter identification from frequency response measurement. After parameter identification, the dominant physical modes are determined by clear stabilization diagrams and clustering tech-nique. In the second step, with prior knowledge of physical poles, the improved frequency-domain maximum likelihood (ML) estimator is presented for building accurate reduced-order model. Before ML estimation, an improved subspace identification considering the poles constraint is also proposed for initializing the iterative procedure. Finally, the performance of the proposed procedure is validated by real flight flutter test data.     

考虑噪声抑制的高超声速风洞气动力识别方法

对于风洞试验中全尺寸模型试验的非平稳信号进行载荷辨识仍存在诸多问题。针对全尺度模型试验的非平稳信号载荷辨识提出了一种基于深度残差收缩网络（DRSN）深度学习技术的智能载荷辨识方法,该方法通过深度学习提取测力系统输出数据中的气动力、惯性力和噪声等特征,通过注意力机制对每组数据进行获取阈值,再通过软阈值函数对特征进行滤波降噪,有效辨识出测力系统响应信号中的惯性力分量并进行剔除,实现气动力载荷辨识。在测试验证中,均值法的辨识精度为85%以上,DRSN模型的辨识精度为94%以上,证明DRSN模型能有效降低噪声和惯性力对于载荷辨识的干扰,用于非平稳信号的载荷辨识具有精度高、可靠性好等特点。     

EBAA：An efficient broadcast authentication scheme for ADS-B communication based on IBS-MR

Automatic dependent surveillance-broadcast （ADS-B） systems can broadcast satellitebased aircraft position, identification, etc., periodically, and are now on track to replace radar to become the backbone of next-generation air traffic management （ATM） systems. However, ADS-B systems suffer severe cyber-security problems due to the broadcast-type data link and the lack of designed-in security measures. Especially, since ADS-B messages are unauthenticated, it is easy to insert fake aircraft into a system via spoofing or insertion of false messages. Unfortu- nately, the authentication for ADS-B messages has not yet been well studied. In this paper, based on identity-based signature with message recovery （IBS-MR）, an efficient broadcast authentication scheme for ADS-B messages is proposed. The security analysis demonstrates that the scheme can achieve authenticity and integrity of ADS-B broadcast messages, as well as adaptive evolution of broadcasters＇ private keys. The performance evaluation shows that the scheme is computationally efficient for typical avionics devices with limited resources. Furthermore, the scheme achieves low communication overhead since broadcast messages can be recovered from signatures, and thus it is suitable for low-bandwidth ADS-B data link.