互相关DPIV亚像素匹配方法研究

使用传统互相关法对DPIV粒子图像进行粗匹配,取得整像素匹配结果,在此基础上开展亚像素定位方法研究.将最小二乘匹配法应用到DPIV技术中,获得比经典的高斯曲面、二次多项式拟合法更高的估算精度,弱化算法对粗匹配相关测度的依赖性.通过控制初始位置和匹配精度降低最小二乘算法的时间开销.标准图像仿真实验以及在氧化沟模型实验中的成功应用,验证了最小二乘匹配法在DPIV技术中的有效性和可靠性.     

惯性信息辅助的快速大视角图像匹配方法

大视角图像匹配算法的鲁棒性与实时性直接影响飞行器对远距离目标定位的性能。针对目前仿射不变图像匹配算法实时性较差的问题,提出一种惯性信息辅助的快速大视角图像匹配方法。该方法对现有的快速图像匹配算法进行改进,避免了构建高斯金字塔,提高了算法效率。然后利用机载惯性导航信息求解实时图与参考图之间的单应性矩阵,并对实时图进行模拟视角变换以此减小图像间视角差异,克服了现有的大视角图像匹配算法盲目多次的匹配计算,实现了大视角图像的快速匹配。实验结果表明,惯性信息辅助的大视角图像匹配算法与现有的快速仿射不变性匹配算法相比,匹配效率提高了至少2倍。     

数字体图像相关方法中基于迭代最小二乘法的物体内部变形测量

本文提出一种基于迭代最小二乘法的亚体素位移测量算法.该算法模型结合了符合实际情况的线性灰度变化模型和线性位移映射函数,采用仅需变形后体图像一阶灰度梯度的迭代最小二乘法计算亚体素位移和位移梯度.由于该算法采用的模型符合实际情况,因而具有更高的位移测量精度和更广泛的适用性.此外,由于仅需变形后体图像的一阶灰度梯度,无需计算...     

基于小波分析与LSSVM的陀螺仪随机漂移建模

为了提高陀螺仪的使用精度,以陀螺仪随机漂移时间序列为研究对象,建立了基于小波分析和最小二乘支持向量机（LSSVM）的陀螺仪随机漂移模型。陀螺仪作为高精度敏感器件,其随机漂移信号具有非线性、弱平稳性等特点,难以补偿。为了提高补偿精度,这里采用小波分析对陀螺仪随机漂移信号进行多尺度分解,利用最小二乘支持向量机方法对重构后的近似序列和细节序列建立非线性子模型,最后将各子模型输出融合作为组合模型输出。最后将该算法用于动调陀螺仪的随机漂移建模,实验结果表明基于该组合算法的非线性模型能够有效地反映陀螺仪的随机漂移特性,建模效果明显优于直接采用LSSVM和ANN建立的模型。     

二维弹性新型快速多极虚边界元的最小二乘法

在虚边界元最小二乘法的方程求解中采用新型的快速多极展开和广义极小残值法,提出了一种二维弹性新型快速多极虚边界元最小二乘法的求解思想。基于二维弹性问题原有的快速多极虚边界元最小二乘法的展开格式,通过引入对角化的概念,以更新展开传递格式;相对于原有快速多极算法,该方法可进一步提高计算效率且仍能保证具有较高的计算精度。数值算例说明了该方法的可行性、计算效率、计算精度均较高。     

基于最小二乘的全局信息融合方法在分布式POS中的应用

分布式POS是一种基于惯性/卫星组合技术的多节点高精度时空测量系统,是实现多任务高精度航空遥感载荷成像的关键装置。受阵风湍流、载机机动等外部扰动,柔性长机翼产生多模挠曲变形,导致柔性基线效应,降低分布式POS多传感器信息融合精度。针对大变形机翼柔性基线效应导致的多传感器信息融合难题,提出了一种基于最小二乘的全局信息融合方法。在分布式POS主子传递对准基础上,采用基于最小二乘的正交多项式拟合方法,对分布式POS所有主子IMU的运动信息进行全局信息融合,充分利用各子IMU对应节点间的空间相关性,得到分布式POS各节点全局估计信息,提高分布式POS测量精度。最后,通过分布式POS地面模拟仿真实验验证,所提出的方法与传递对准方法相比,x轴基线精度平均提高了1.893 mm,y轴基线精度平均提高了0.461 mm,z轴基线精度平均提高了2.183 mm,水平姿态测量精度平均提高0.023°。     

基于移动相关的最小二乘地图匹配新算法

为了提高军用车辆导航数字地图匹配的精度,针对通常匹配方法易出现误匹配和无法消除沿道路方向纵向误差的问题,提出了一种基于移动相关的最小二乘地图匹配新方法。该方法充分利用路网和历史轨迹信息,以多分辨率移动相关性进行匹配路段的搜索和定位,以最小二乘法进行SINS轨迹到待配路段的曲线整体投影,并通过视觉和数学的方法消除车辆偏离道路中心线的偏差影响。跑车实验表明,匹配后定位圆误差极限在1 m以内。该算法简单有效,且能满足高精度的要求,可以为组合导航提供良好辅助信息。     

一种基于视觉的道路宽度测量方法

自动驾驶技术的研究中,为了快速检测到道路并测量出道路的宽度,提出了一种基于视觉的道路宽度测量方法。首先提出了一种改进的Deeplabv3+语义分割算法,在原算法流程中引入了基于空间域的注意机制,提高了道路边缘分割的精度。其次,提出了一种结合直方图均衡化和加权最小二乘滤波的半全局立体匹配算法,显著提高了图像中物体边缘细节的匹配精度。基于所提出的方法搭建了道路宽度测量系统,该系统搭载在自动驾驶车辆上完成了对全域图像中道路的分割和宽度测量。实验结果表明,所提出算法的道路宽度测量误差不超过真实值的5.0%。     

基于光电测量的双站系统多目标跟踪

为了提高多目标跟踪的跟踪精度以及解决传统雷达多目标跟踪方法中杂波数目过多的缺陷,提出一种基于光电测量的双站系统多目标跟踪方法。首先设计了一种利用矩形关联门确定双站视野内目标数目的算法,然后利用加权最小二乘法实现对量测信息进行融合并与关联门进行匹配筛选,最后采用改进的联合概率密度数据关联算法对融合数据进行处理,实现对多个目标的实时跟踪。实验结果表明,该方法可以确定视野内的目标数目并且相比于最小二乘法提高了86.6%的跟踪精度。     

基于遗传算法的机翼柔性蒙皮全参数优化设计

为解决变弯度机翼前缘柔性蒙皮结构设计问题,提出基于遗传算法的柔性蒙皮全参数优化方法。采用"刚度剪裁"设计理念,以大型远程飞机前缘为研究对象,通过优化变量缩减、设计区域规划和边界条件位移等效,对柔性蒙皮结构进行工程简化,在保证变形精度的同时达到降低模型复杂度的目的;基于遗传算法对蒙皮结构进行全参数同步优化,以获得混合优化变量的全局最优解。研究表明,该方法在兼顾优化效率和制造可实现的基础上,使前缘蒙皮变形的最小二乘误差(LSE)降低60%,最大偏移误差降低64%,可显著提高变形精度。     

Digital Image Correlation Using Stochastic Parallel-Gradient-Descent Algorithm

This article proposes a digital image correlation (DIC) method based on the stochastic parallel gradient descent (SPGD) algorithm. Stochastic parallel perturbations are imposed on deformation parameters to make the correlation coefficients converge to a global extremum; thus, this allows the final measured values of the deformation parameters to be obtained and the DIC measurement to be made. Both simulated and real data processing, including rigid body and strain deformation, show that the proposed method can achieve nearly the same accuracy as the Newton–Raphson (NR) method in most cases and higher accuracy in some cases, such as the simulated experiments of rigid body translation with and without noise. It also has a good noise-robustness. Furthermore, a series of experiments have been designed to evaluate the convergence characteristics of the proposed method, and it has been proved able to process large displacement and have a stable convergence process, good robustness, and a high convergence speed when bilinear interpolation is adopted.     

大型结构变形实时摄像测量方法

本文对实时测量大型结构静力变形实验中如何应用摄像测量方法展开研究。针对实时摄像测量的两个主要难题研究解决方法,即图像特征点自动提取和多像机图像特征点自动对应。通过在待测结构表面粘贴LED发光灯或使用激光光栅投影做为合作标志点,提出NNLOG(normalnized negative laplacian of gaussian)算子用于图像上合作标志点的实时提取与跟踪;根据多摄像机约束关系,构造对极几何约束代价函数,解决多像机图像特征点之间的对应问题。设计实现了精度实验,表明位移测量误差小于1mm,相对误差小于1%,基于本文方法实现的测量系统已应用于某型飞机静力变形实验。     

Fast, Robust and Accurate Digital Image Correlation Calculation Without Redundant Computations

High-efficiency and high-accuracy deformation analysis using digital image correlation (DIC) has become increasingly important in recent years, considering the ongoing trend of using higher resolution digital cameras and common requirement of processing a large sequence of images recorded in a dynamic testing. In this work, to eliminate the redundant computations involved in conventional DIC method using forward additive matching strategy and classic Newton–Raphson (FA-NR) algorithm without sacrificing its sub-pixel registration accuracy, we proposed an equivalent but more efficient DIC method by combining inverse compositional matching strategy and Gauss-Newton (IC-GN) algorithm for fast, robust and accurate full-field displacement measurement. To this purpose, first, an efficient IC-GN algorithm, without the need of re-evaluating and inverting Hessian matrix in each iteration, is introduced to optimize the robust zero-mean normalized sum of squared difference (ZNSSD) criterion to determine the desired deformation parameters of each interrogated subset. Then, an improved reliability-guided displacement tracking strategy is employed to achieve further speed advantage by automatically providing accurate and complete initial guess of deformation for the IC-GN algorithm implemented on each calculation point. Finally, an easy-to-implement interpolation coefficient look-up table approach is employed to avoid the repeated calculation of bicubic interpolation at sub-pixel locations. With the above improvements, redundant calculations involved in various procedures (i.e. initial guess of deformation, sub-pixel displacement registration and sub-pixel intensity interpolation) of conventional DIC method are entirely eliminated. The registration accuracy and computational efficiency of the proposed DIC method are carefully tested using numerical experiments and real experimental images. Experimental results verify that the proposed DIC method using IC-GN algorithm and the existing DIC method using classic FA-NR algorithm generate similar results, but the former is about three to five times faster. The proposed reliability-guided IC-GN algorithm is expected to be a new standard full-field displacement tracking algorithm in DIC.     

基于Fuzzy ARTMAP神经网络的景像匹配实时图选取方法

提出一种新的基于Fuzzy ARTMAP神经网络并利用图像直方图特征的快速景像匹配实时图选取方法。与已有的方法相比,该方法充分考虑了图像的边缘、亮度、对比度、信噪比等特征对影像实时图质量的影响,具有自适应聚类、收敛导速,实时性好,分类准确率高和通用性强等优点。将该方法应用于SMGS（景像匹配制导系统）进行实时图像的自动选取,可大大提高SMGS的智能性,可靠性和实时性。     

一种考虑旋转位移分量的数字图像相关法及其精度分析

提出了一种新的考虑旋转位移分量的数字图像相关法[CD2]旋转相关匹配法,其特点是先对图像子区进行预旋转,再进行相关匹配、相关系数、整像素和亚像素位移的计算。在物体产生旋转位移分量时,该方法可有效提高变形前后图像子区间的相关系数和位移计算精度。通过斜拉伸、剪切和悬臂梁弯曲实验,对旋转相关匹配法和直接相关匹配法进行了对比研究,并用灰度梯度法计算旋转后新图像子区和变形后图像子区间的亚像素位移。结果表明,在旋转位移分量小于10°的情况下,相比于直接相关匹配法,旋转相关匹配法可以得到更高的相关系数;在用灰度梯度法计算亚像素位移条件下,位移精度与试件位移不产生旋转时的直接相关匹配相当。     

颗粒材料接触特性之接触点的确定

颗粒物质在自然界中普遍存在,如砂砾、谷物、堆石体和碎屑流等,许多自然现象和工业过程都与颗粒物质的运动状态有关。弄清颗粒之间的接触特征是理解颗粒变形与运动规律的关键,与之相关联的接触点确定是获取全场接触力(包括力链)信息的难点。近年来,光弹法逐渐成为这类问题研究的有效手段之一,原因在于该方法具有原理简单、操作方便、图像直观等优点。然而,已有的接触点判定方法主要依赖于圆盘圆心距离的计算,对于小变形圆盘接触特征难以有效识别。为此,本文发展了一种基于去除零级条纹区域及图像矩阵转换的算法,可以有效地确定接触点的位置。主要步骤如下:首先运用主成分分析方法对图像进行分析,提取主成分,并重构原图像;然后利用模板匹配方法提取各个光弹圆盘,接着对提取出来的各个圆盘进行图像矩阵变换;最后对变换后的图像局部进行垂直方向灰度梯度平方计算,描绘梯度变化曲线并提取曲线峰值,从而识别出接触点(位置)。     

舰载姿态加角速度匹配传递对准方法研究

用于传递对准的测量参数匹配法极大地受限于舰船所处海况，为解决这一问题，提出了姿态加角速度匹配法。在三种典型的海况下，对这一传递对准方法中舰船甲板变形和陀螺常值漂移进行了Kalman滤波估计及精度分析，并对陀螺漂移标定的可行性进行了深入的分析。研究结果表明，姿态加角速度匹配法具有稳健的对准精度和快速性，陀螺漂移的标定依赖于舰船甲板动态变形的大小。     

粒子图像测速技术互相关算法研究进展

粒子图像测速技术(particle image velocimetry, PIV)中采用的互相关算法就是需要从独立 存在的两幅图像通过一定的判别方法得到流场中各点的流速矢量的计算方法. 互相关算法的具体实现步骤包括图像前处理、区域离散、 匹配原则选取、搜索方法选取和变形预测, 最后对结果进行后处理. 文中从上述几个方面总 结了国内外近年来互相关算法的发展过程, 并通过对各种方法精度和效率的比较对其应用发 展进行了归纳.     

Full-field speckle pattern image correlation with B-Spline deformation function

A full-field speckle pattern image correlation method is presented that will determine directly the complete, two-dimensional deformation field during the image correlation process on digital images obtained using computer vision systems. In this work, a B-Spline function is used to represent the object deformation field throughout the entire image area. This is an improvement over subset-based image correlation methods by implicitly maintaining position and derivative continuity constraints among subsets up to a specified order. The control point variables within the B-Spline deformation function are optimized iteratively with the Levenberg-Marquardt method to achieve minimum disparity between the predicted and actual deformed images. Results have shown that the proposed method is computationally efficient, accurate and robust. The general framework of this method can be applied ton-dimensional image correlation systems that solve for multi-dimension vector fields.     

Multi-frame pyramid correlation for time-resolved PIV

A novel technique is introduced to increase the precision and robustness of time-resolved particle image velocimetry (TR-PIV) measurements. The innovative element of the technique is the linear combination of the correlation signal computed at different separation time intervals. The domain of the correlation signal resulting from different temporal separations is matched via homothetic transformation prior to the averaging of the correlation maps. The resulting ensemble-averaged correlation function features a significantly higher signal-to-noise ratio and a more precise velocity estimation due to the evaluation of a larger particle image displacement. The method relies on a local optimization of the observation time between snapshots taking into account the local out-of-plane motion, continuum deformation due to in-plane velocity gradient and acceleration errors. The performance of the pyramid correlation algorithm is assessed on a synthetically generated image sequence reproducing a three-dimensional Batchelor vortex; experiments conducted in air and water flows are used to assess the performance on time-resolved PIV image sequences. The numerical assessment demonstrates the effectiveness of the pyramid correlation technique in reducing both random and bias errors by a factor 3 and one order of magnitude, respectively. The experimental assessment yields a significant increase of signal strength indicating enhanced measurement robustness. Moreover, the amplitude of noisy fluctuations is considerably attenuated and higher precision is obtained for the evaluation of time-resolved velocity and acceleration.