基于兼容性网格分割的骨骼参数计算

为了解决骨骼参数难以测量的问题,提出一种利用网格分割结果计算参数的方法.首先对骨骼网格模型在提取少量特征点的基础上进行语义分割;然后将分割得到的模板借助基于Laplacian变形的非刚性配准,指导同类骨骼模型实现快速兼容性分割;最后结合网格分割结果及特征点计算出骨骼的主要形态参数.实验结果表明,该方法仅需少量的用户交互就能获得较好的测量效果,结合模板的策略也支持大批量骨骼模型的参数测定.     

基于环境激励的桥梁振动模态识别算法研究

在桥梁建造和维护过程中,需要对桥梁的振动模态进行在线、实时的分析,急需一种不需要人工激励进行快速模态分析的算法。通过研究自然激励技术NExT( Natural Excitation Technique)与自回归滑动平均模型ARMA( Auto￣Regressive and Moving Average Model),在常规的自然环境模态分析算法的基础上构造出一种快速求解NExT￣ARMA模型的算法进行桥梁模态识别。相比于传统的环境激励模态参数计算方法,该算法不但降低了传统算法的复杂度,而且采用了反馈的方式提高了计算精度。采用ANSYS建立有限元模型并搭建简易实验系统分别对该算法进行仿真验证和实验验证,验证结果表明,该算法能够有效地在自然激励下提取出桥梁结构的各阶模态,其中对前三阶固有频率的识别相对误差降到1％左右。     

HY-2高度计海况偏差非参数估计模型研究

基于HY-2高度计数据,采用局部线性回归非参数估计方法,利用球谐核函数及局部可调带宽,对70和71周期的交叉点进行海况偏差非参数估计。依据解释方差、海况偏差与有效波高及风速的相关度和模型残差分析,检验评价模型。与相同数据集下的参数模型估计结果进行了分析比对,结果表明:所选定的非参数模型的海况偏差与有效波高和风速的相关度均处于较高水平,说明模型更为有效。在不同纬度段,非参数模型和参数模型各有所长,在北半球高纬度区域,非参数模型表现更优。     

嵌入式时栅传感器高精度激励设计方法

介绍了嵌入式时栅传感器的基本原理,分析了两相激励信号不一致性主要是幅值不等和相位不正交对传感器测量精度的影响。基于DDS原理结合反馈控制设计了高精度的激励信号模块,采用反馈电路控制可程控放大电路调理两相信号幅值,实现了激励信号的幅值相等,基于闭环反馈控制直接修改数字激励信号实现了信号的相位正交。实验研究结果表明,采用这种闭环控制的方法,传感器短周期测角误差从±65″降低到±16″左右,常值误差基本消除,传感器精度大幅度提高。     

Semiglobal stabilization of saturated linear systems via multiple parametric Lyapunov equations

This paper investigates the problem of semiglobal stabilization with guaranteed flexible pole placement for saturated linear systems. To retain the advantages of the parametric Lyapunov equation, matrix‐partitioning idea is used to derive a new pole shift lemma. Starting from system matrix transformations, a recursive algorithm is proposed to shift every eigenvalue of a linear system separately without mode decomposition in each step. A new method introducing various parameters to every Lyapunov equation in each step is presented. As an application, the semiglobal stabilization with guaranteed flexible pole placement for saturated linear systems can be achieved by this method. Finally, its effectiveness and advantages are demonstrated via a simulation example. Copyright © 2013 John Wiley & Sons, Ltd.     

铰支柔性梁主参数共振的时滞反馈控制

研究了时滞反馈控制作用下铰支柔性梁主参数共振问题.采用多尺度法,从理论上推导了时滞位移反馈控制作用下铰支柔性梁非线性主参数共振,分析了时滞、反馈控制增益,非线性系数等系统参数对系统非线性主参数振动的影响,分析了主参数动力响应随参数变化的规律.结果表明:随着反馈增益的增大,系统响应幅值得到明显抑制,合理地控制系统参数选取可提高振动控制的效率.     

时滞反馈作用下压电梁的参数共振分析

基于Hamilton原理建立了受控压电梁的参数振动方程,研究了轴向激励压电梁时滞速度反馈控制的主参数共振.采用非线性振动的多尺度法研究了压电梁的亚谐波主参数共振,并对其稳定域进行分析.通过算例分析得到了不同时滞,控制增益,轴力影响下压电梁参数共振的稳定域和时程曲线.结果表明:时滞值增大,系统承受轴向力减小,相对于控制增益则反之.同时,随着轴向力增大,在一定范围内主动阻尼增加,时滞反馈能有效降低响应幅值.随着时滞值增大,减振效果变差.     

基于知识工程模板的月牙肋岔管参数化设计

基于CATIA软件的知识工程技术,提出了月牙肋钢岔管的三维参数化设计方法。选取合适的定位条件,并通过建立参数关联实现用户输入参数与草图、三维模型之间的驱动关系,建立了通用的月牙肋岔管的设计模板。采用该模板可以快速确定月牙肋岔管多种设计方案,并导入有限元软件进行结构分析,获得最终设计方案。在三维模型上进行焊缝分缝设计后,借助曲面展开功能获得管节展开图,并自动生成控制点坐标表和材料表。该设计方法以建立模板为核心,整合了岔管参数化建模、有限元结构分析、焊缝分缝设计和绘制岔管展开图四大功能,满足了月牙肋岔管施工详图阶段的设计需求,在工程应用中显示了设计效率高的优点。     

Parametric Stabilization of Quantized Interconnected Systems with Application to Coupled Inverted Pendulums

This paper studies the analysis of parametric stability and decentralized state feedback control of a kind of quantized interconnected systems. The output of each controller is quantized logarithmically before it is input to the subsystem, and the quantized density would affect the stability of the systems. First, a decentralized state feedback controller is designed for interconnected systems without quantization and the corresponding stable region is obtained. Second, for a given controller, the lower bound of the quantization density is evaluated from parameters of local controllers. Finally, the proposed method is applied to coupled inverted pendulums systems which can be viewed as quantized interconnected systems. The simulation results show that by using the proposed quantized controllers, the interconnected inverted pendulum systems are parametrically stabilized.     

Parametric modeling of microwave passive components using combined neural networks and transfer functions in the time and frequency

A novel parametric modeling technique is proposed to develop combined neural network and transfer function models for both time and frequency (TF) domain applications of passive components, where the neural network is trained to map geometrical variables to the coefficients of transfer functions. Built on our previous work, a new order‐changing module is developed to enforce stability of transfer functions and simultaneously guarantee continuity of coefficients. A constrained optimization strategy is introduced to enforce passivity of transfer functions through a neural network training process. A general equivalent circuit for two‐port passive components is generated directly from coefficients of arbitrary‐order transfer functions. Once trained, the parametric model can provide accurate and fast prediction of the electromagnetic behavior of passive components with geometrical parameters as variables. Compared to our previous work, the proposed method enables models to work well in the time domain providing good accuracy in challenging modeling applications. Two parametric modeling examples of spiral inductors and interdigital capacitors, and their application in both time and frequency domain simulations of a power amplifier are examined to demonstrate the validity of the proposed technique. © 2012 Wiley Periodicals, Inc. Int J RF and Microwave CAE , 2013.