Cubic B样条旋转曲面的自由绘制技术

随着基于样条曲线的模型逐渐成为CAGD的主要研究对象,进一步带动了高度自由曲面建模技术的发展.本文描述一个新颖、直观的旋转曲面绘制技术,它支持三次B样条的自由输入作为轮廓线,并通过提取的样点矢量以及最小方差逼近方法形成旋转轴,利用轴上测量点的切线方向确定各个圆平面,从而建立了平面上旋转坐标矩阵,最终插值空间球面样点生成双三次B样条曲面.实验结果有效地验证了此技术的高效性.     

基于径向基函数与B样条的散乱数据拟合方法

针对散乱数据的曲面拟合问题,提出一种径向基函数与B样条插值结合使用的曲面拟合方法.通过分片径向基函数插值,三维散乱点,再从分片插值曲面上获取预先设定好的有序网格点的值,最后利用张量积B样条插值有序网格点,从而得到拟合曲面.该方法较好地解决散乱数据插值和拟合的计算不稳定性问题,最后给出算法实例.     

二元三次样条曲面的C1光滑拼接

在一元三次样条曲线的基础上,提出了二元三次样条曲面的构造,可对多块曲面片作C1光滑拼接,用于各种工业外形的造型设计。     

基于一维插值的人头像三维表面重建

描述了一种基于一维插值的人头像三维表面的重建方法。该方法从几个不同侧面的人体头部条形图获得人头像的三维条形图．经过型值点的提取，一维三次样条插值，三维重建，进而得到任意分辨率的人体头部三维曲而的数字表示及三角形、四边形网格图等表示形式，一维插值与传统的三维曲面重建的二维插值方法相比较，算法简单，三维曲面重建所需的时间也较少。该方法已在PIII 800PC机上进行了验证，获得了较好的效果。     

基于三次样条插值的硅压阻式压力传感器的温度补偿

传感器的零点温度漂移、灵敏度温度漂移和非线性误差是影响传感器性能的主要因素,如何能使该类误差得到有效补偿对于提高其性能有重要意义。提出了基于三次样条曲线插值的温度补偿方法,改进了传统三次样条曲线插值的补偿方法,分别对传感器的零点、灵敏度以及非线性进行补偿,用这种方法对测压范围为1.0140×105 Pa～3.0140×105 Pa,温度范围为-20℃～+60℃的硅压阻式压力传感器的实验标定结果进行了温度补偿。通过比较传统三次样条插值补偿后的传感器输出信号,验证了使用改进后的三次样条曲线插值法的补偿效果更好。这种方法为高精度压力传感器的温度补偿提供了一种有价值的理论依据。     

基于遗传小波神经网络的压力传感器的非线性校正研究

为了消除压力传感器受非目标参量的影响而呈现的非线性特性,利用小波神经网络来完成压力传感器的非线性校正.利用遗传算法对小波神经网络权阈值优化,以提高网络精确度和训练速度,设计了遗传优化小波神经网络,将该网络用于压力传感器的非线性校正.仿真结果表明该方法能有效消除非目标参量对传感器输出结果的影响.压力传感器的精度和准确度都得到提高.该系统不但可以用于各类传感器的非线性校正,还可用于其它类似系统.且设计、实现简单,适于工程应用,具有实际应用价值.     

三次B样条插值曲面及其实现

目前在ＣＡＭ／ＣＡＭ的自由曲面构造方法中，较流行的有Ｂ样条曲面，Ｂｅｚｉｅｒ曲面、Ｂａｌｌ曲面等方法，但由这几种方法和成都是拟合曲面，而百插值曲面，常常不能满足一些工程实际中严格插值的要求，本文构造了一种自由插值曲面生成方法－Ｂ样条母线法，所生成曲面达到Ｃ＾２级光滑，适用机械，模具、汽车、造船等制造加工行业的复杂曲面设计。     

不规则网格上的曲面设计方法

提出一种在不规则网格上构造曲面的方法.其基本思想是,通过均匀双三次B样条基函数的分解和子基函数的分类,将B样条曲面方法推广到任意四边形网格.给定一个任意四边形控制网格,首先对每个控制点构造一个基函数;所有控制点加权组合形成整体曲面.构造的曲面是分片双三次有理参数多项式曲面.此方法可以看成是均匀B样条曲面构造方法的扩展,如果控制网格是规则四边形网格,那么构造得到的曲面与均匀双三次B样条曲面是一致的.最后,实例证明此方法能够有效地构造曲面.     

在VC中研究双三次B样条曲面

双三次B样条曲面在汽车、飞机等行业的机体曲面外形设计中起着巨大的作用,本文首先在理论方面对曲线和曲面,特别是对双三次B样条曲面进行了详尽的阐述,然后在VC环境下对其进行具有实际运用价值的探讨与研究。     

SnO2 纳米传感器的灵敏度􀀁温度特性曲线拟合研究

对三次样条函数在纳米传感器输出特性曲线拟合中的应用进行了理论分析,应用软件Matlab6.5结合实验数据对掺杂苯的SnO2纳米传感器的灵敏度-温度特性曲线进行了拟合,结果表明三次样条曲线函数的拟合曲线光滑且精度高,相对误差在-0.2%～ 0.3%以内.     

A fast regularization parameter selection for regularly sampled 2D inputs

A fast method of computing the regularization parameter is proposed for the case where the radial basis function network is used for image interpolation by putting the regularly sampled pixel as the two-dimensional input and the pixel value as the output. A performance index is minimized by using the steepest descent method to find the optimal regularization parameter. The choice of regularly sampled two-dimensional input data allows a significant reduction in computation time with the properties of a Kronecker product.     

基于观测器的移动执行器对二维分布参数系统的控制

研究二维分布参数系统在传感器执行器网络下的控制问题.传感器执行器网络由二维平面上固定的传感器与移动的执行器组成.首先,利用传感器对二维分布参数系统的测量信息设计观测器,用来估计二维分布参数系统的状态,并在观测器的基础上给出相应的控制器;然后,利用算子半群理论并结合Lyapunov方法,得到平面上移动的执行器的水平运动速度和垂直运动速度,该速度依赖于观测器的信息;最后,数值仿真表明,二维分布参数系统在该移动执行器控制下的性能得到了有效的提高.     

基于B 样条曲面插值误差控制的内超环面齿轮齿面建模

针对内超环面齿轮齿面数控加工精度难以保证的问题,提出一种基于B 样条曲面 插值误差控制的内超环面齿轮齿面建模的方法。该方法以内超环面齿轮理论齿面原型为依据, 运用B 样条曲面构造插值曲面,计算插值曲面片与理论齿面之间的误差。通过插值误差分析, 根据误差分布特点,将型值点网格不断细化,获得一组型值点阵,经插值重构后可得到满足精 度要求的内超环面齿轮齿廓模型。最后,通过数控加工验证了建模的有效性。基于B 样条曲面 插值误差控制的内超环面齿轮齿面建模方法为获得高精度的内超环面齿轮实体模型奠定了理 论基础。     

基于静力测试的三维曲面结构测点优化配置

传感器测点优化配置在结构健康监测系统中具有重要作用。针对结构健康监测中静力作用下三维曲面结构变形状况进行了研究,提出了三维曲面结构的测点优化配置方法。首先,对三维曲面结构进行测点组合选取,根据已知测点的响应值采用三维超曲面样条函数插值估计未布置测点的响应值,然后建立适应度函数,对未布置测点的估计值与实际值的误差进行判定,最后通过二重结构编码遗传算法对测点组合进行优化,选取适应度函数值最小的测点配置方案,从而实现了传感器测点优化配置的目的。应用该方法对简支的圆柱壳弯曲变形进行了测点优化配置,得到的适应度函数值最小的测点配置方案中,未布置测点的估计值与实际值的误差为1.10％,从而验证了该方法的可行性和有效性。     

Guaranteed-quality anisotropic mesh generation for domains with curved boundaries

Anisotropic mesh generation is important for interpolation and numerical modeling. Recently, Labelle and Shewchuk proposed a two-dimensional guaranteed-quality anisotropic mesh generation algorithm called a Voronoi refinement algorithm. This algorithm treats only domains with straight lines as inputs. In many applications, however, input domains have many curves and the exact representation of curves is required for efficient numerical modeling. In this paper, we extend the Voronoi refinement algorithm and propose it as a guaranteed-quality anisotropic mesh generation algorithm for domains with curved boundaries. Some experimental results are also shown.     

基于二元多项式拟合法的压力传感器输入信号重构

为了同时解决压力传感器输出特性的非线性和温度漂移问题,提出利用二元多项式根据传感器输出信号及其内部温度来重构被测压力.给出了被测压力重构模型的具体形式,以传感器静态特性标定试验数据为依据,利用最小二乘法求解模型系数矩阵,利用单点最大拟合误差、误差平方和模型阶次三项指标进行模型择优.基于重构模型给出了测量电路检测精度估算方法.本方法在传感器静态特性标定数据范围内得到了便于工程计算的一致表达式,同时解决了传感器的非线性和温度漂移两个主要问题,计算所用数据量大大小于插值法.某型硅谐振压力传感器的应用验证了本方法的合理性和有效性.     

Three-dimensional Visual Mapping of Underwater Ship Hull Surface Using Piecewise-planar SLAM

In-water visual ship hull inspection using unmanned underwater vehicles needs to be performed at very close range to the target surface because of the visibility limitations in underwater environments mainly due to light attenuation, scattering, and water turbidity. These environmental challenges result in ineffective photometric and geometric information in hull surface images and, therefore, the performance of conventional three-dimensional (3D) reconstruction techniques is often unsatisfactory. This paper addresses a visual mapping method for 3D reconstruction of underwater ship hull surface using a monocular camera as a primary mapping sensor. The main idea of the proposed approach is to model the moderately curved hull surface as a combination of piecewise-planar panels, and to generate a global map by aligning the local images in a two-dimensional reference frame and correcting them appropriately to reflect the information of perspective projections of the 3D panels. The estimated 3D panels associated with the local images are used to extract the loop-closure relative measurements in the framework of simultaneous localization and mapping (SLAM) for precise camera trajectory estimation and 3D reconstruction results. The validity and practical feasibility of the proposed method are demonstrated using a dataset obtained in a field experiment with a full-scale ship in a real sea environment.

     

局部形状可调插值曲线曲面及其参数选取方案

以形状可调插值曲线曲面为研究主题的文献多数侧重于分析曲线曲面性质,少有文献介绍可调插值曲线曲面的构造方法,以及调节参数的选取方案。这里以3次Hermite插值曲线为基础,通过在导矢中引入参数来构造形状可调插值曲线,将曲线按照插值数据进行整理,即可得到含参数的插值基函数,进而由之构造张量积插值曲面。为了帮助设计者寻找合适的参数,提供了4种用于确定曲线中形状参数的准则,其中的3种还推广应用于曲面,每种准则都提供了可以直接使用的公式。所给可调插值曲线曲面的构造方法以及参数选取方案具有一般性,数值实例验证了方案的有效性。     

Identification of space curves from two-dimensional perspective views

This paper describes a new method to be used for matching three-dimensional objects with curved surfaces to two-dimensional perspective views. The method requires for each three-dimensional object a stored model consisting of a closed space curve representing some characteristic connected curved edges of the object. The input is a two-dimensional perspective projection of one of the stored models represented by an ordered sequence of points. The input is converted to a spline representation which is sampled at equal intervals to derive a curvature function. The Fourier transform of the curvature function is used to represent the shape. The actual matching is reduced to a minimization problem which is handled by the Levenberg-Marquardt algorithm [3].     

Two and three-dimensional intrusion object detection under randomized scheduling algorithms in sensor networks

We are interested in wireless sensor networks which are used to detect intrusion objects such as enemy tanks, cars, submarines, etc. Since sensor nodes have a limited energy supply, sensor networks are configured to put some sensor nodes in sleep mode to save energy. This is a special case of a randomized scheduling algorithm. Ignored by many studies, an intrusion object’s size and shape are important factors that greatly affect the performance of sensor networks. For example, an extremely large object in a small sensor field can easily be detected by even one sensor node, no matter where the sensor node is deployed. The larger an intrusion object is, the fewer sensor nodes that are required for detection. Furthermore, using fewer sensor nodes can save resources and reduce the waste of dead sensor nodes in the environment. Therefore, studying coverage based on intrusion object’s size is important. In this paper, we study the performance of the randomized scheduling algorithm via both analysis and simulation in terms of intrusion coverage intensity. In particular, we study cases where intrusion objects occupy areas in a two-dimensional plane and where intrusion objects occupy areas in a three-dimensional space, respectively. We also study the deployment of sensor nodes when intrusion objects are of different sizes and shapes. First, sensor nodes are deployed in a two-dimensional plane and a three-dimensional space with uniform distributions. Then, they are deployed in a two-dimensional plane and a three-dimensional space in two-dimensional and three-dimensional Gaussian distributions, respectively. Therefore, our study not only demonstrates the impact of the size and shape of intrusion objects on the performance of sensor networks, but also provides a guideline on how to configure sensor networks to meet a certain detecting capability in more realistic situations.