LEAST-SQUARES METHOD-BASED FEATURE FITTING AND EXTRACTION IN REVERSE ENGINEERING

The main purpose of reverse engineering is to convert discrete data pointsinto piecewise smooth, continuous surface models. Before carrying out model reconstruction it issignificant to extract geometric features because the quality of modeling greatly depends on therepresentation of features. Some fitting techniques of natural quadric surfaces with least-squaresmethod are described. And these techniques can be directly used to extract quadric surfaces featuresduring the process of segmentation for point cloud.

PCR ALGORITHM FOR PARALLEL COMPUTING MINIMUM-NORM LEAST-SQUARES SOLUTION OF INCONSISTENT LINEAR EQUATIONS

This paper presents a new highly parallel algorithm for computing the minimum-norm least-squares solution of inconsistent linear equations Ax = b(A∈Rm×n,b∈R (A)). By this algorithm the solution x = A + b is obtained in T = n(log2m + log2(n - r + 1) + 5) + log2m + 1 steps with P=mn processors when m × 2(n - 1) and with P = 2n(n - 1) processors otherwise.

A LOW-COST OPTIMIZATION APPROACH FOR SOLVING MINIMUM NORM LINEAR SYSTEMS AND LINEAR LEAST-SQUARES PROBLEMS

Recently,the authors proposed a low-cost approach,named Optimization Approach for Linear Systems(OPALS)for solving any kind of a consistent linear system regarding the structure,characteristics,and dimension of the coefficient matrix A.The results obtained by this approach for matrices with no structure and with indefinite symmetric part were encouraging when compare with other recent and well-known techniques.In this work,we proposed to extend the OPALS approach for solving the Linear Least-Squares Problem(LLSP)and the Minimum Norm Linear System Problem(MNLSP)using any iterative low-cost gradient-type method,avoiding the construction of the matrices AT A or AAT,and taking full advantage of the structure and form of the gradient of the proposed nonlinear objective function in the gradient direction.The combination of those conditions together with the choice of the initial iterate allow us to produce a novel and efficient low-cost numerical scheme for solving both problems.Moreover,the scheme presented in this work can also be used and extended for the weighted minimum norm linear systems and minimum norm linear least-squares problems.We include encouraging numerical results to illustrate the practical behavior of the proposed schemes.

ON THE BREAKDOWNS OF THE GALERKIN AND LEAST-SQUARES METHODS

The Galerkin and least-squares methods are two classes of the most popular Krylov subspace methOds for solving large linear systems of equations. Unfortunately, both the methods may suffer from serious breakdowns of the same type: In a breakdown situation the Galerkin method is unable to calculate an approximate solution, while the least-squares method, although does not really break down, is unsucessful in reducing the norm of its residual. In this paper we first establish a unified theorem which gives a relationship between breakdowns in the two methods. We further illustrate theoretically and experimentally that if the coefficient matrix of a lienar system is of high defectiveness with the associated eigenvalues less than 1, then the restarted Galerkin and least-squares methods will be in great risks of complete breakdowns. It appears that our findings may help to understand phenomena observed practically and to derive treatments for breakdowns of this type.

Estimation of mass transfer coefficient in ozone absorption by linear least square fitting and Simplex search methods

For physical ozone absorption without reaction,two parametric estimation methods,i.e.the common linear least square fitting and non-linear Simplex search methods,were applied,respectively,to determine the ozone mass transfer coefficient during absorption and both methods give almost the same mass transfer coefficient.While for chemical absorption with ozone decomposition reaction,the common linear least square fitting method is not applicable for the evaluation of ozone mass transfer coefficient due to the difficulty of model linearization for describing ozone concentration dissolved in water.The nonlinear Simplex method obtains the mass transfer coefficient by minimizing the sum of the differences between the simulated and experimental ozone concentration during the whole absorption process,without the limitation of linear relationship between the dissolved ozone concentration and absorption time during the initial stage of absorption.Comparison of the ozone concentration profiles between the simulation and experimental data demonstrates that Simplex method may determine ozone mass transfer coefficient during absorption in an accurate and high efficiency way with wide applicability.

Linear-fitting-based similarity coefficient map for tissue dissimilarity analysis in T2^＊-w magnetic resonance imaging

Similarity coefficient mapping（SCM） aims to improve the morphological evaluation of T＊2weighted magnetic resonance imaging（T＊2-w MRI）. However, how to interpret the generated SCM map is still pending. Moreover, is it probable to extract tissue dissimilarity messages based on the theory behind SCM？ The primary purpose of this paper is to address these two questions. First, the theory of SCM was interpreted from the perspective of linear fitting. Then, a term was embedded for tissue dissimilarity information. Finally, our method was validated with sixteen human brain image series from multiecho T＊2-w MRI. Generated maps were investigated from signal-to-noise ratio（SNR） and perceived visual quality, and then interpreted from intra- and inter-tissue intensity. Experimental results show that both perceptibility of anatomical structures and tissue contrast are improved. More importantly, tissue similarity or dissimilarity can be quantified and cross-validated from pixel intensity analysis. This method benefits image enhancement, tissue classification, malformation detection and morphological evaluation.

Research on the Model of Linear Data Fitting Method

By using the method of least square linear fitting to analyze data do not exist errors under certain conditions, in order to make the linear data fitting method that can more accurately solve the relationship expression between the volume and quantity in scientific experiments and engineering practice, this article analyzed data error by commonly linear data fitting method, and proposed improved process of the least distance squ^re method based on least squares method. Finally, the paper discussed the advantages and disadvantages through the example analysis of two kinds of linear data fitting method, and given reasonable control conditions for its application.

A fault recognition method based on clustering linear regression

Aiming at the problems of low accuracy,long time consumption,and failure to obtain quantita-tive fault identification results of existing automatic fault identification technic,a fault recognition method based on clustering linear regression is proposed.Firstly,Hough transform is used to detect the line segment of the enhanced image obtained by the coherence cube algorithm.Secondly,the endpoint of the line segment detected by Hough transform is taken as the key point,and the adaptive clustering linear regression algorithm is used to cluster the key points adaptively according to the lin-ear relationship between them.Finally,a fault is generated from each category of key points based on least squares curve fitting method to realize fault identification.To verify the feasibility and pro-gressiveness of the proposed method,it is compared with the traditional method and the latest meth-od on the actual seismic data through experiments,and the effectiveness of the proposed method is verified by the experimental results on the actual seismic data.

基于线结构光扫描的烟支表面缺陷检测方法研究

在烟支表面缺陷检测时,为解决传统二维图像方法无法获得深度信息的问题,提出一种基于线结构光传感器旋转扫描的检测方法。烟支在两同向辊轮的旋转带动下实现自转,通过线结构光视觉传感器获取物体轴向轮廓线,使用随机采样一致性拟合轮廓线,通过计算原始点到拟合轮廓的距离判断缺陷点。选取某品牌烟支在检测过程中得到的原始数据,其中多组样本的Kappa值均达到0.97,重复性达到99.3%。研究为烟支缺陷检测提供参考。

基于幂加权最小二乘拟合的红外相机辐射定标方法

分析了现有线性度计算方法的不足,提出基于偏差/测量值的新线性度评价方式,通过该方式最小二乘拟合的低端温度偏差比高端大一个数量级,并采用加权拟合提高系统响应线性度。在分析不同光谱的温度和辐亮度拟合函数基础上,提出一种基于辐亮度倒数幂加权最小二乘线性拟合的地面和星上辐射定标方法,确认最佳权重幂次,建立了幂次n=1的加权最小二乘拟合外黑体线性定标方程、内黑体线性定标方程、内外黑体辐亮度转换模型。针对星上内黑体高精度两点定标建立了基于加权最小二乘拟合内外黑体辐亮度转换模型;针对星上黑体发射率退化提出了基于恒星定标的红外相机星上内黑体辐亮度定标修正方法,建立了外黑体辐亮度、内黑体辐亮度和恒星辐亮度转换模型。采用加权线性拟合后,积分时间10 ms的低温端外黑体反演偏差由1.63 K下降到0.52 K,内黑体偏差反演温度偏差由0.83 K下降到0.39 K,系统响应线性度明显提升。

基于FPGA的多通道温度采编装置设计

针对飞行试验中对设备温度测量的需求,设计了一种适用于飞行测试的高精度多通道温度采编装置。设计以FPGA构建信号采集处理系统,采用AD8227和AD590来实现信号的调理和温度冷端补偿,通过标准RS422协议实现16路温度信号传输,并采取线性拟合的方式对输出进行非线性校正,提高了系统准确率和稳定性。测试结果表明,测温电路全量程内最大测量误差为±0.083%F.S.。经过测试验证,该方案传输过程无丢帧零误码,系统运行高效、可靠。

基于曲线拟合误差估计的阻抗优化识别方法

在雷达系统、舰船系统、数据中心等大型复杂系统中,供配电系统变流器端口阻抗信息的完整、快速、准确获取,是研判系统可靠性的重要基础。现有研究大都使用分段线性拟合值方法进行阻抗识别,不仅需要大量阻抗测量才能获得完整的阻抗特性,并且可能因过度测量而对系统的正常运行造成干扰。针对这些问题,从阻抗特性曲线的非线性拟合入手,提出一种“非线性曲线拟合、全局误差估计、优选测量点频率”的阻抗识别方法,实现基于曲线拟合误差估计的测量点优化选择,以较少阻抗测量代价获取宽频带阻抗特性。与现有的方法相比,所提方法更有助于测量点的合理选择、阻抗谐振峰的准确识别,从而更高效地实现宽频带阻抗的识别,为复杂供配电系统运行状况的研判提供可靠依据。算例仿真证实了所提方法的有效性。

基于电压-电流采样轨迹的混合直流输电线路纵联保护方法

为提高混合直流输电系统线路保护的抗干扰能力和适用范围,提出一种基于电压-电流采样轨迹的直流输电线路保护方案。首先,从理论上分析了直流线路故障时测量电压与测量电流之间的关系,揭示了区内/外故障时的电压-电流线性度差异。然后,以区外故障时电压-电流所服从的线性模型作为假设模型,将实测数据得到的采样轨迹与假设模型对应的直线进行比对,引入拟合优度指标作为特征量来量化并放大实测数据与假设模型的差异,并进一步给出直流输电线路保护方案。最后,在PSCAD/EMTDC中建模并仿真分析了多种因素对所提保护方案的影响,结果表明所提保护方案能够可靠、快速地识别直流输电线路故障,在高阻和强噪声的场景下仍可适用,且无需提取特征频带,无需双端数据严格同步,对于保护装置的采样率要求较低,易实现工程应用。

“两尘四气”空气污染数据的校准模型

通过Excel软件对监测点收集的空气质量数据进行拆分及构造函数的方法,拟合了“两尘四气”的六个方程,这些方程可用于对自建点数据进行校准。在对所收集的数据标准化后,利用SPSS软件对“两尘四气”数据误差产生的原因进行回归分析,建立了多元线性回归方程。方程显示:压强、温度和风速更容易导致自建点数据误差,可使用对上述三种因素不敏感的材质制造检测仪的传感器。以上使用Excel和SPSS软件对大数据进行比对处理及建模的方法可用于环境监测、农业生产等领域促进高质量生态文明建设。

FDM全彩3D打印的色彩调控方法研究

传统熔融沉积(FDM)3D打印工艺由于材料的单一性,无法按需成型彩色模型。现有“三进一出”的FDM混色机构,由于色域空间的不同、原材料的色彩偏差及混色机构的差异性采用直接三基色混色方式导致实际打印色彩与理论色彩间存在较大偏差。针对这一问题,基于FDM三基色混色喷头,通过色域空间转换建立色彩与FDM打印工艺间的关系;通过打印实验对转换模型进行线性拟合修正,进而建立面向FDM全彩3D打印的色彩配置库,通过模型颜色与库中颜色的匹配,实现三维模型设计色彩到打印色彩的精确转换。

一种提高整体拟合程度的对数分布广义翁氏模型新解法

广义翁氏模型已有解法在进行参数优选线性拟合时普遍存在生产初期拟合点离散偏差性较强的问题,这些偏差点与整体拟合趋势线的偏离程度较大,且偏差点的位置相对较为集中,加大了偏差点对整体拟合程度的影响,进一步影响了模型参数的优选准确性。针对模型已有解法存在的问题,本文从模型拟合点的分布形式研究出发,提出了一种对数分布广义翁氏模型新解法,区别于已有解法以时间t作为线性拟合函数自变量,新解法以时间对数ln(t)作为线性函数的自变量,拟合点的分布形态也从均匀分布转变为对数分布。实际应用表明,新解法使生产初期参数拟合点分布相对更加分散,分布趋势也更贴近整体拟合点的趋势,参数拟合初期拟合点偏离误差平均值减少了2.1%,参数拟合曲线整体偏离误差平均值减少了1.7%,模型新解法对应的产量偏离误差较模型已有解法平均值减少2.87%,表明模型新解法相对模型已有解法更能够提高产量的整体拟合程度。

城市道路工况全触屏模式下空调操作风险特性

针对全触屏空调操作给驾驶过程带来的潜在风险,以典型城市道路工况为对象,设计搭建了全触屏和传统人机交互两类驾驶实验平台,采集了19名被试在40、60 km/h速度情况下的空调操作过程人-车系统数据。采用单因素方差分析和线性拟合对数据进行分析。结果表明:与按键式相比,触屏式完成任务总时间(T TD)更长;单次注视时间(S GD)大于1.5 s的占比增大20%左右,车辆运行风险更大;方向盘转角标准差(S DSWA)更小,接近于0。单次手部操作时间(S HOD)与次任务步骤数呈正比关系;随车速增加,按键模式下次任务的单次注视时间(S GD)大于1.5 s占比减少10%左右,车辆运行风险降低;完成任务总时间(T TD)、单次注视时间(S GD)及单次手部操作时间(S HOD)的均值数据均无显著变化。因此,在全触屏交互界面普及的今天,应保留处理空调类操作任务的按键,并优化按键布局或按动效果。

基于时间线性拟合的地缆架空混合线路的行波故障定位

目的研究n段地缆架空混合输电线路中行波故障定位问题,提出一种基于时间线性拟合的行波故障定位方法。方法首先对故障区域进行判断,确定故障所在的区域,其次再将不同波阻抗线路进行归一化处理,减少因波速不同而产生的测距误差,最后使用时间线性拟合的方法对故障进行精确定位。结果解决了初始行波波头识别困难的问题,也减小了行波速度随传输距离变化而变化带来的测距误差问题。结论在MATLAB/Simulink中搭建一个500 kV的地缆架空混合输电线路仿真模型,实验的验证结果表明此故障定位方法能够有效地解决因行波速度不同而导致的双端行波测距方法不适用问题,最终实现对故障点的精确定位。

一种基于线性回归的雷达航迹跟踪算法

针对雷达航迹跟踪过程中精度与实时性难兼顾的问题,提出了一种基于线性回归的雷达航迹跟踪算法。线性回归作为一种简单有效的建模方法,可用于预测与推断,与雷达航迹跟踪模型一致。工程实践数据表明,该算法对目标运行轨迹拟合度高,跟踪精度高,实用性强。

基于改进灰度重心法的线结构光中心提取算法

针对传统算法无法准确提取线结构光条中曲率变化较大区域中心线的缺陷,提出了一种基于改进灰度重心法的线结构光中心线提取算法。基于阈值法提取感兴趣区域和开闭运算滤除图像中的噪声点,获取质量相对较高的待处理图像;利用灰度重心法提取光条中心点,得到初始坐标并设置一个矩形计算区域,根据最小二乘法计算每个初始点的方向向量和法向量;在设定的矩形区域内计算初始点在其法线方向上的偏移量,得到精确的中心点坐标。实验结果表明:提出的算法能在线结构光中心中曲率变化较大区域精确提取中心线,提取精度均值为0.096 pixels,精度比率为44.2%,平均提取速度为0.082 s。