识别传递函数参数的一种广义最小二乘法

线性动力学系统的频响特性的量测误差具有相关性,用最小二乘估计求得的传递函数系数有偏.为此,本文用广义最小二乘法导出识别传递函数参数的迭代算法,并用数值模拟法产生强噪声污染的频响函数数据,用它作识别计算.结果表明本文建议的算法比最小二乘法的精度有明显提高,计算量也不大.     

基于MATLAB的蜂窝纸板缓冲包装系统参数辨识

通过正弦振动试验,研究了蜂窝纸板缓冲包装系统的振动特性,获得了蜂窝纸板的振动传递率曲线。采用MATLAB软件,利用最小二乘法对振动传递函数中的fn和c进行辨识,得到了理论传递率函数,并与试验数值进行了对比分析,证明了运用MATLAB和最小二乘法识别蜂窝纸板系统参数是可行的,具有较高的精度。利用识别出的固有频率和阻尼系数,对不同尺寸的蜂窝纸板进行了预测,预测结果与试验结果比较接近。     

自激振动系统的参数识别

自激振动是一种特殊的振动形式,为了使自激振动能够得到控制,需要对该系统进行参数识别。我们将自激振动的近似解作为数学模型来进行曲线拟合,通过寻求参数的最优值使目标函数的值最小,来获得系统要识别的参数。本文用计算机求出自激系统的数值解作为测量值来模拟整个参数识别过程,模拟识别的例子表明用最优化方法来进行参数识别的计算,精度是较高的。     

舰用燃气轮机框架模型的模态参数识别

本文采用一次有理正交多项式－多模态曲线合法对一舰用燃气轮机框架模型进行了实验模态分析，以Ｆｏｒｓｙｔｈｅ复合交多项式作为频响函数的理论值，用实测的频响函数建立系数矩阵，来寻找使目标函数最小的最优值，本文在ＨＰ９８２６微机上建立了建立了测试，数据采集及参数识别等系统识别软件，给出了具有工程实用意义的前五阶振动模态参数，识别结果和有限元计算相比较，令人满意。     

局部非线性刚度阻尼系统参数识别的一种新方法

研究了具有平方非线性刚度和平方非线性阻尼的两自由度局部非线性振动系统，采用空间法来识别该系统模型的参数。利用该方法对非线性频响函数进行估计，并利用最小二乘法对模型的非线性刚度系数和非线性阻尼系数进行了优化，实验结果表明了该方法的可行性，在识别和优化汽车等局部非线性系统的物理参数方面具有一定的参考价值。     

参数振动系统频响特性研究

采用矩阵谱分解中常用的Sylvester理论和Fourier级数展开法,推导了单自由度参数振动系统的频响函数,并得到了系统外激励共振条件。在此基础上,以直齿轮副参数振动系统为例仿真了系统的频响特性,并讨论了系统参数稳定性、时变参数以及阻尼的影响。结果表明,参数振动系统的频响特性主要有以下一些特点:(1)系统具有多个频响函数,分别对应于多频响应中的各个频率成分;(2)系统存在多个外激励共振区。除了外激励频率等于系统固有频率的共振区外,当激励频率等于系统固有频率与参数激励频率的组合值时,同样存在共振现象;(3)参数振动系统共振响应时,主导频率成分为系统固有频率;(4)阻尼使得频响函数峰值有明显下降,而对非共振区的频响曲线影响不大。     

线性结构振动亏损系统的实验模态分析

本文设计了一个用速度反馈实现粘性阻尼的结构振动系统并进行了实验和模态参数识别，实验模态分析结果表明，具有非比例阻尼的结构振动系统，在欠阻尼范围内，系统是可以成为亏损的；对于亏损系统，其频响特性只有用广义模态理论才能正确地描述。     

用局部点振动数据重构系统物理参数

本文提出用系统的局部振动测量来识别其物理参数的一种方法。文章首先运用微分方程的算子解法，将描述结构振动的动力学方程转化为由测量点信号表示的输入输出系统参数模型，并建立该模型参数─—系统参数与物理参数间的对应关系，然后运用系统辨识技术识别出该系统参数，最后利用系统参数与物理参数间的映射关系，反推出待识别系统的物理参数。     

随机振动下产品包装系统的传递路径数值仿真与实验研究

针对产品内部质量分布不均、材料和结构特性不同,建立产品包装系统模型,通过数值仿真和实验研究产品包装系统的振动传递特性,并探究在限带白噪声谱和ASTM卡车运输谱激励下产品包装系统的振动响应规律。利用状态空间法和MATLAB/Simulink仿真工具对产品包装系统进行随机振动仿真分析,研究缓冲衬垫材料参数对路径的频响传递函数和产品动态响应的影响。研究结果表明：在产品的四条振动传递路径中,刚度和质量分布大的路径上的频响传递函数和质量块的振动响应更大;产品内部的阻尼参数对各路径的频响传递函数和质量块的加速度响应基本无影响;关键元件上的加速度响应大小介于产品各路径上质量块的加速度响应大小之间;较大的缓冲衬垫阻尼有利于降低关键元件上加速度响应功率谱（PSD）的共振峰大小,较大的缓冲衬垫刚度使关键元件响应PSD共振频率和共振峰值均增大。外部激励谱型、系统的振动传递特性和共振频率附近的激励谱能量对缓冲衬垫的减振效果均有影响。仿真分析和实验研究下的产品包装系统的随机响应规律具有一致性。     

混沌激励下振动系统的非线性参数识别

本文对基于时-频相结合的非线性振动系统的参数识别问题进行了研究。首先建立含非线性参数单自由度振动系统的力学模型,将已知非线性系统产生的混沌响应作为该系统的激励, 假定其响应有若干不稳定的周期轨道组成,从混沌响应的状态空间中提取出近似周期轨道, 采用谐波平衡法识别出系统的参数,然后对识别出的参数进行误差分析。最后通过数值模拟,验证了混沌信号作为激励源对非线性系统进行参数识别的可行性。     

Covariance matrix adapted evolution strategy algorithm-based solution to dynamic economic dispatch problems

This article presents a covariance matrix adapted evolution strategy (CMAES) algorithm to solve dynamic economic dispatch (DED) problems. The DED is an extension of the conventional economic dispatch problem, in which optimal settings of generator units are determined with a predicted load demand over a period of time. In this article, the applicability and validity of the CMAES algorithm is demonstrated on three DED test systems with a sequential decomposition approach. The results obtained using the CMAES algorithm are compared with results obtained using the real-coded genetic algorithm, the Nelder–Mead simplex method, and other methods from the literature. To compare the performance of the various algorithms, statistical measures like best, mean, worst, standard deviation, and mean computation time over 20 independent runs are taken. The effect of population size on the performance of the CMAES algorithm is also investigated. The simulation experiments reveal that the CMAES algorithm performs better in terms of fuel cost and solution consistency. Karush–Kuhn–Tucker conditions are applied to the solutions obtained using the CMAES algorithm to verify optimality. It is found that the obtained results satisfy the Karush–Kuhn–Tucker conditions and confirm optimality.     

A wavelet-based multisensor data fusion algorithm

This paper presents a wavelet transform-based data fusion algorithm for multisensor systems. With this algorithm, the optimum estimate of a measurand can be obtained in terms of minimum mean square error (MMSE). The variance of the optimum estimate is not only smaller than that of each observation sequence but also smaller than the arithmetic average estimate. To implement this algorithm, the variance of each observation sequence is estimated using the wavelet transform, and the optimum weighting factor to each observation is obtained accordingly. Since the variance of each observation sequence is estimated only from its most recent data of a predetermined length, the algorithm is self-adaptive. This algorithm is applicable to both static and dynamic systems including time-invariant and time-varying processes. The effectiveness of the algorithm is demonstrated using a piecewise-smooth signal and an actual time-varying flow signal.     

Structural damage detection using ARMAX time series models and cepstral distances

A novel damage detection algorithm for structural health monitoring using time series model is presented. The proposed algorithm uses output-only acceleration time series obtained from sensors on the structure which are fitted using Auto-regressive moving-average with exogenous inputs (ARMAX) model. The algorithm uses Cepstral distances between the ARMAX models of decorrelated data obtained from healthy and any other current condition of the structure as the damage indicator. A numerical model of a simply supported beam with variations due to temperature and operating conditions along with measurement noise is used to demonstrate the effectiveness of the proposed damage diagnostic technique using the ARMAX time series models and their Cepstral distances with novelty indices. The effectiveness of the proposed method is validated using the benchmark data of the 8-DOF system made available to public by the Engineering Institute of LANL and the simulated vibration data obtained from the FEM model of IASC-ASCE 12-DOF steel frame. The results of the studies indicate that the proposed algorithm is robust in identifying the damage from the acceleration data contaminated with noise under varied environmental and operational conditions.     

Measurement Uncertainty: Methods and Applications

We consider the problem of determining an optimal experimental design for estimation of parameters of a class of complex curves characterizing nanowire growth that is partially exponential and partially linear. Locally D-optimal designs for some of the models belonging to this class are obtained by using a geometric approach. Further, a Bayesian sequential algorithm is proposed for obtaining D-optimal designs for models with a closed-form solution, and for obtaining efficient designs in situations where theoretical results cannot be obtained. The advantages of the proposed algorithm over traditional approaches adopted in recently reported nanoexperiments are demonstrated using Monte Carlo simulations. The computer code implementing the sequential algorithm is available as supplementary materials.     

利用自适应阵对空间信号测向

给出一种基于Gram Schmidt正交 (GSO)结构的自适应测向方法 ,分辨力与特征值分解类算法相当。在测向的过程中 ,不需要事先知道或估计信号源的个数 ,算法简单 ,实时性好     

Gaining-Sharing Knowledge Based Algorithm for Solving Stochastic Programming Problems

This paper presents a novel application of metaheuristic algorithms for solving stochastic programming problems using a recently developed gaining sharing knowledge based optimization (GSK) algorithm. The algorithm is based on human behavior in which people gain and share their knowledge with others. Different types of stochastic fractional programming problems are considered in this study. The augmented Lagrangian method (ALM) is used to handle these constrained optimization problems by converting them into unconstrained optimization problems. Three examples from the literature are considered and transformed into their deterministic form using the chance-constrained technique. The transformed problems are solved using GSK algorithm and the results are compared with eight other state-of-the-art metaheuristic algorithms. The obtained results are also compared with the optimal global solution and the results quoted in the literature. To investigate the performance of the GSK algorithm on a real-world problem, a solid stochastic fixed charge transportation problem is examined, in which the parameters of the problem are considered as random variables. The obtained results show that the GSK algorithm outperforms other algorithms in terms of convergence, robustness, computational time, and quality of obtained solutions.     

Inverse scattering and diffraction tomography in cylindrical background media

A recently developed inverse scattering method based on the distorted-wave Born approximation (DWBA) that applies to objects embedded in known background media [Inverse Probl.19, 855 (2003);20, 1307 (2004)] is implemented for the special case of circularly symmetric scatterers embedded in circularly symmetric backgrounds. The newly developed scheme is applied in a computer-simulation study of optical diffraction tomography (ODT), and the results are compared and contrasted with reconstructions obtained using the filtered backpropagation algorithm (FBP algorithm). Unlike the DWBA-based inversion algorithm, the FBP algorithm does not take into account multiple scattering within the known background, and it is found that the newly implemented scheme yields reconstructions much superior to those obtained using the FBP algorithm. The research reported applies to a number of important applications that include ultrasound nondestructive evaluation testing of cylinders for defects as well as ODT.     

An order batching algorithm for wave picking in a parallel-aisle warehouse

In this paper we address the problem of batching orders in a parallel-aisle warehouse, with the objective to minimize the maximum lead time of any of the batches. This is a typical objective for a wave picking operation. Many heuristics have been suggested to solve order batching problems. We present a branch-and-bound algorithm to solve this problem exactly. An initial upper bound for the branch-and-bound algorithm is obtained using a 2-opt heuristic. We present a basic version of the algorithm and show that major improvements are obtained by a simple but very powerful preprocessing step and an improved lower bound. The improvements for the algorithm are developed and tested using a relatively small test set. Next, the improved algorithm is tested on an extensive test set. It appears that problems of moderate size can be solved to optimality in practical time, especially when the number of batches is of importance. The 2-opt heuristic appears to be very powerful, providing tight upper bounds. Therefore, a truncated branch-and-bound algorithm would suffice in practice.     

Plane-wave expansion method for calculating band structure of photonic crystal slabs with perfectly matched layers

We present a new algorithm for calculation of the band structure of photonic crystal slabs. This algorithm combines the plane-wave expansion method with perfectly matched layers for the termination of the computational region in the direction out of the plane. In addition, the effective-medium tensor is applied to improve convergence. A general complex eigenvalue problem is then obtained. Two criteria are presented to distinguish the guided modes from the PML modes. As such, this scheme can accurately determine the band structure both above and below the light cone. The convergence of the algorithm presented has been studied. The results obtained by using this algorithm have been compared with those obtained by the finite-difference time-domain method and found to agree very well.     

The iterative group implicit algorithm for parallel transient finite element analysis

The Iterative Group Implicit (IGI) algorithm is developed for the parallel solution of general structural dynamic problems. In this method the original structure is partitioned into a number of a subdomains. Each subdomain is solved independently and therefore concurrently, using any traditional direct solution method. The IGI algorithm is an extension of the Group Implicit (GI) algorithm, and similarly to that method compatibility of the interface degrees of freedom is restored using a mass averaging rule. However, unlike the GI algorithm, in the IGI algorithm an iterative procedure is devised to restore equilibrium at the interface degrees of freedom. The IGI method has the same algorithmic characteristics as the underlying solution method used to solve each subdomain. Furthermore, the solution obtained by this method, once the iteration converges, is the same as the one obtained if the subdomain solution method is used to solve the whole structure. Numerical studies are carried out which demonstrate that the performance of the IGI algorithm is superior to that of the GI algorithm both in terms of accuracy and efficiency. Finally, the IGI method is highly modular and scalable, and therefore very well suited for distributed and parallel computing. Copyright © 2000 John Wiley & Sons, Ltd.