基于单像素成像的微小位移测量方法

激光散斑位移测量法是一种重要的现代光学位移测量方法,由于受到图像传感器元件感光性能限制,难以在强干扰光条件下获得有效散斑场信息,进而无法获取位移场数据,因此,基于单像素成像技术,本文提出一种新的激光散斑位移测量方法:对散斑信息进行图案编码调制,并使用单像素探测器采集调制后的光强信息;利用Walsh-Hadamard Transformation(WHT)成像算法对散斑场图像进行重建;最后结合自相关算法确定物体的位移场信息。分别利用商业相机和单像素成像技术对散射介质的单轴微小位移进行测量,结果表明基于单像素成像技术的激光散斑位移测量技术可以获得较好的测量结果。相比于传统测量方法,基于单像素成像技术的激光散斑位移测量方法在复杂环境中具有一定的优势,可实现强光干扰下的位移场测量。     

数字全息粒子图像测速技术(DHPIV)研究进展

全息粒子图像测速技术(DHPIV)是当前非常具有发展潜力的非定常三维流场测量技术,是一种具有点空间分辨力的三维空间三维速度场和时间历程的实验观测方法和技术. 本文介绍了该项技术(数字全息DH和粒子图像测速PIV)的发展背景和近20年来的研究进展,并介绍了已测得的非定常复杂流动的初步结果. 详细论述了DHPIV技术所面临的关键性问题和应用基础问题以及相应的进展:粒子空间场的重建与再现的空间分辨率问题、粒子定位或位移精度问题、信噪比和数字再现的光学与快速算法以及测量空间的扩展等问题.同时讨论了数字离轴全息等有关技术的潜力, 介绍了进一步的研究发展方向.      

PIV速度场坏矢量的本征正交分解处理技术

介绍了一种针对粒子图像测速(PIV)基于本征正交分解(POD)的速度场后处理技术.该技术改变了现在后处理技术将速度场坏矢量识别和修正分开实现的局面,通过迭代方法有效地实现了速度场坏点统一的识别和修复算法.算法利用POD分解的低阶模态信息重构出可以用于坏矢量识别的参考速度场,利用该参考速度场对全流场进行坏点识别并完成修正.通过对一套光滑的PIV速度场数据引入高斯分布的随机误差,测试验证了该POD方法的优越性.在坏矢量识别方面新方法较归一化中值检验有更高的正确性,能识别大面积出现的坏矢量区域.在坏矢量修补的插值算法中,新方法的计算效率又高于传统Gappy POD方法,且计算精度优于常见的矢量场内插数学方法.特别是在数据缺失的大连通区域,该方法对物理流场有很好的预测效果.     

稳定分层二层流室内实验早期格栅湍流结构

采用室内实验混合箱和粒子图像测速技术,本文研究了稳定分层无平均剪切二层流(上层淡水、下层盐水)振动湍流结构.对实验录像进行粒子图像测速技术处理,获得垂向二维流场(垂直于格栅平面)瞬时速度和涡量,并用于计算:①时均速度和时均涡量;②均方根速度;③均匀程度和各向同性程度;④平均流强度;⑤时均泰勒的欧拉积分长度尺度;⑥时均湍...     

实验流体力学的粒子成像技术

<正> 1 引言 现代实验流体力学的一个重大成就是,发明并发展了整个标量场和矢量场的瞬态测量技术.这些技术包括测量标量的层析摄影干涉测量法(tomographic interferometry)(Hessetink1988)和平面激光诱发荧光法(Hassa et al 1987),以及测量速度场的核磁共振成像法(Leeet al 1987),平面激光诱发荧光法,激光散斑测速法,粒子跟踪测速法,分子跟踪测速     

散斑图像相关数字技术原理及应用

研究图像处理技术在散斑测量中的应用，提出了一种散斑图像相关数字技术，该方法引进了亚像素技术，采用重心算法计算特征斑的重心，避免了数字散斑相关法计算相关系数的繁复过程；应用位移和应变的有关公式，可以获得物体变形实验曲线，实验结果表明，该方法在工程实际现场、振动过程以及变形测量的自动化等方面有着广泛的应用潜力，从而为光测力学拓展应用领域、实现自动化测量展现了新的前景。     

基于非均匀查询窗口PIV技术的湍流边界层特性实验研究

粒子图像测速技术以及互相关图像查询算法在湍流边界层测量中应用广泛,而均匀查询窗口(Interrogation Window,IW)较强的空间平均作用提高了IW对速度数据的尺度敏感性。根据量纲为一的速度的相对不确定度构造与局部平均速度相适应的非均匀IW模型,结合图像变形技术,形成IW法向尺寸随法向位置或速度梯度变化的IW布局。利用DNS槽道流对该方法的性能进行评估,通过Re_θ=355,440,538的平板湍流边界层PIV实验,对比不同IW方法的湍流边界层特性结果差异。结果表明:相比于均匀IW方法结果,非均匀IW方法有效提高了近壁面的空间分辨率和位移精度,获得了准确的湍流统计量信息,识别出了更完整的涡结构并提升了湍流结构中含能结构的能量获取能力。非均匀IW在边界层测量中表现出了更好的性能,这对于充分的解析边界层至关重要。     

气液两相流中气泡运动速度场的PIV分析与研究

粒子图像测速技术（PIV）作为一种无扰、瞬态、全场速度测量方法，已被广泛应用于液体或气体的单相流流速场测定。对于两相流PIV技术，目前还处于起步阶段，本文应用PIV技术的基本原理，对静止液体中的气泡运动速度进行了分析，并对有关气液两相流测量问题进行了探讨。     

二维粒子图像测速系统的研制

研制了一套二维粒子图像测速系统,该系统采用CCD对流场中的示踪粒子视频图像进行采集,以拓扑映射的新方法完成料粒子像对的匹配;整个过程无需人工干预,处理结果声速、准确、可靠,如每处理一幅图像仅需5分钟,匹配准确度达95％以上,其结果可给出被测流场的速度分量、速度矢量、等流函数线和等涡线等。该系统与业已建成的多相分离实验模拟系统相配套,可用来对多种设备内流场进行多参数、多工况实验诊断,为揭示设备工作机理、优化设备结构等提供了有效手段。     

基于非线性光流方程的高阶时域DIC算法

针对极端测试环境中采集的低质量测试图像,提出一种解析高精度变形场的高阶时域DIC(Digital Image Correlation)算法.采用模拟散斑方法建立了含高斯白噪声的亚像素级位移图像,通过最小二乘迭代法求解高阶时域DIC算法的位移量,分析了算法的测试精度.研究结果表明,非线性光流方程能够描述变形前后像素点灰度...     

Particle image velocimetry with optical flow

 An optical Flow technique based on the use of Dynamic Programming has been applied to Particle Image Velocimetry thus yielding a significant increase in the accuracy and spatial resolution of the velocity field. Results are presented for calibrated synthetic sequences of images and for sequences of real images taken for a thermally driven flow of water with a freezing front. The accuracy remains better than 0.5 pixel/frame for tested two-image sequences and 0.2 pixel/frame for four-image sequences, even with a 10% added noise level and allowing 10% of particles of appear or disappear. A velocity vector is obtained for every pixel of the image. Received: 18 July 1997/Accepted: 5 December 1997     

Development and validation of echo PIV

The combination of ultrasound echo images with digital particle image velocimetry (DPIV) methods has resulted in a two-dimensional, two-component velocity field measurement technique appropriate for opaque flow conditions including blood flow in clinical applications. Advanced PIV processing algorithms including an iterative scheme and window offsetting were used to increase the spatial resolution of the velocity measurement to a maximum of 1.8 mm×3.1 mm. Velocity validation tests in fully developed laminar pipe flow showed good agreement with both optical PIV measurements and the expected parabolic profile. A dynamic range of 1 to 60 cm/s has been obtained to date.     

A method for automatic estimation of instantaneous local uncertainty in particle image velocimetry measurements

The uncertainty of any measurement is the interval in which one believes the actual error lies. Particle image velocimetry (PIV) measurement error depends on the PIV algorithm used, a wide range of user inputs, flow characteristics, and the experimental setup. Since these factors vary in time and space, they lead to nonuniform error throughout the flow field. As such, a universal PIV uncertainty estimate is not adequate and can be misleading. This is of particular interest when PIV data are used for comparison with computational or experimental data. A method to estimate the uncertainty from sources detectable in the raw images and due to the PIV calculation of each individual velocity measurement is presented. The relationship between four error sources and their contribution to PIV error is first determined. The sources, or parameters, considered are particle image diameter, particle density, particle displacement, and velocity gradient, although this choice in parameters is arbitrary and may not be complete. This information provides a four-dimensional “uncertainty surface” specific to the PIV algorithm used. After PIV processing, our code “measures" the value of each of these parameters and estimates the velocity uncertainty due to the PIV algorithm for each vector in the flow field. The reliability of our methodology is validated using known flow fields so the actual error can be determined. Our analysis shows that, for most flows, the uncertainty distribution obtained using this method fits the confidence interval. An experiment is used to show that systematic uncertainties are accurately computed for a jet flow. The method is general and can be adapted to any PIV analysis, provided that the relevant error sources can be identified for a given experiment and the appropriate parameters can be quantified from the images obtained.     

Visualisation of air–water bubbly column flow using array Ultrasonic Velocity Profiler

In the present work, an experimental study of bubbly two-phase flow in a rectangular bubble column was performed using two ultrasonic array sensors, which can measure the instantaneous velocity of gas bubbles on multiple measurement lines. After the sound pressure distribution of sensors had been evaluated with a needle hydrophone technique, the array sensors were applied to two-phase bubble column. To assess the accuracy of the measurement system with array sensors for one and two-dimensional velocity, a simultaneous measurement was performed with an optical measurement technique called particle image velocimetry(PIV). Experimental results showed that accuracy of the measurement system with array sensors is under 10% for one-dimensional velocity profile measurement compared with PIV technique. The accuracy of the system was estimated to be under 20% along the mean flow direction in the case of two-dimensional vector mapping.     

Comparison between Digital Fresnel Holography and Digital Image-Plane Holography: The Role of the Imaging Aperture

Optical techniques are now broadly used in the field of experimental mechanics. The main advantages are they are non intrusive and no contact. Moreover optical techniques lead to full spatial resolution displacement maps enabling the computing of mechanical value also in high spatial resolution. For mesoscopic measurements, digital image correlation can be used. Digital holographic interferometry is well suited for quantitative measurement of very small displacement maps on the microscopic scale. This paper presents a detailed analysis so as to compare digital Fresnel holography and digital image-plane holography. The analysis is based on both theoretical and experimental analysis. Particularly, a theoretical analysis of the influence of the aperture and lens in the case of image-plane holography is proposed. Optimal filtering and image recovering conditions are thus established. Experimental results show the appropriateness of the theoretical analysis.     

A model-based validation framework for PIV and PTV

The utility of particle image velocimetry (PIV) for measurement of velocity fields in many fluid flows is well established. This has created interest in overcoming difficulties with the technique when applied to increasingly larger fields of view where there exists a significant range of velocities and spatial velocity gradients are large. In this regard, a major deficiency with standard cross-correlation PIV is the inherent link between the density of vectors in the measurement field and the maximum measurable displacement. Several schemes exist to reduce this link. These iterative hierarchical/multiresolution schemes are strongly dependent on vector validation routines to remove spurious vectors. Here the design of a new framework for vector validation is described. This framework is general enough for use with both regular and irregularly spaced vector fields to make it applicable to particle image velocimetry (PIV), particle tracking velocimetry (PTV), and hybrid methods. It is based on the determination of a smoothed displacement field that robustly characterizes the measured field such that invalid vectors are attenuated more than valid vectors. In this particular study a thin-plate spline model is incorporated within an iterative regularized weighted least-squares routine to find a smoothed version of the displacement field that maintains pertinent velocity gradient information. The utility of the methodology is demonstrated for a complex flow profile containing four vortices where the valid displacement ranges from ?1/4 to +1/4 of the area of interest (AOI) dimension. Results indicate that this validation strategy can discriminate between valid and invalid vectors remarkably well over a range of parameter settings. In the example presented a flow field with significant velocity gradients and having a high number of invalid vectors (25%) is accurately validated.     

Pseudo turbulence in PIV breaking-wave measurements

 The particle image velocimetry (PIV) technique was employed to measure the instantaneous velocity distribution under nonbreaking and breaking water waves. The corresponding turbulence intensity was calculated by the ensemble average of repeated measurements. The pseudo turbulence found was large enough to affect the accuracy of the turbulence measurements. We follow Prasad et al.'s (1992) approach to demonstrate that the pseudo turbulence is related to the bias error, which is the discrepancy between the true position of the particle image and the position calculated from the pixel array data with inadequate pixel resolution. To reduce the bias error (or the pseudo turbulence), we first calculate it from a turbulence-free flow with the same experimental set-up as that used for the targeted experiments (i.e., we use the same size of field of view, seeding particles, seeding density, lens aperture, and laser wavelength in both experiments). Then we minimize the bias error from the turbulence measurements in the actual experiments. To demonstrate the procedure, the evolution of a breaking wave is investigated. Received: 30 January 1998/Accepted: 28 October 1999     

Tomographic particle image velocimetry

This paper describes the principles of a novel 3D PIV system based on the illumination, recording and reconstruction of tracer particles within a 3D measurement volume. The technique makes use of several simultaneous views of the illuminated particles and their 3D reconstruction as a light intensity distribution by means of optical tomography. The technique is therefore referred to as tomographic particle image velocimetry (tomographic-PIV). The reconstruction is performed with the MART algorithm, yielding a 3D array of light intensity discretized over voxels. The reconstructed tomogram pair is then analyzed by means of 3D cross-correlation with an iterative multigrid volume deformation technique, returning the three-component velocity vector distribution over the measurement volume. The principles and details of the tomographic algorithm are discussed and a parametric study is carried out by means of a computer-simulated tomographic-PIV procedure. The study focuses on the accuracy of the light intensity field reconstruction process. The simulation also identifies the most important parameters governing the experimental method and the tomographic algorithm parameters, showing their effect on the reconstruction accuracy. A computer simulated experiment of a 3D particle motion field describing a vortex ring demonstrates the capability and potential of the proposed system with four cameras. The capability of the technique in real experimental conditions is assessed with the measurement of the turbulent flow in the near wake of a circular cylinder at Reynolds 2,700.     

Theory of non-isotropic spatial resolution in PIV

The spatial resolution of the PIV interrogation technique is discussed from an analytical standpoint and assessed with Monte Carlo numerical simulation of particle image motion. The PIV measurement error associated with lack of spatial resolution is modelled associating the cross-correlation operator to a moving average filter. The error associated with the "low-pass filtering" effect is investigated by adopting a second-order polynomial expression for the velocity spatial distribution. According to the present error analysis, the measurement error is proportional to the second-order spatial derivative of the velocity field and increases with the square of the window linear size. The strategy for the selection of the window size and properties (aspect ratio and orientation) so as to minimize the error is discussed. The principle is based on nonisotropic interrogation windows of elliptical shape, with a constant area and elongated in the direction of the largest curvature radius. The nonisotropic parameters are defined as eccentricity and orientation, which are based on the local eigenvalues/vectors of the Hessian tensor of the displacement spatial distribution. The technique is implemented in a recursive PIV interrogation method. The performance of nonisotropic interrogation technique is assessed by means of synthetic PIV images, which simulate three situations: first, a one-dimensional sinusoidal shear displacement, which allows comparison of the cross-correlation spatial response with the transfer function of linear filters. Second, the stream-wise exponential velocity decay is simulated, which simulates the particle tracers decelerating downstream of a shock wave and gives an example of a flow with main velocity differences aligned with the velocity direction. The results show that keeping the image density fixed, the error caused by insufficient spatial resolution can be reduced by a factor two when a preferential direction is found in the flow field. Finally, a Lamb–Oseen vortex flow is presented, which shows the complex pattern formed by the interrogation windows in a two-dimensional case. In this case, the improvement in interrogation performance is limited due to the isotropic nature of the velocity spatial fluctuation.     

Three-component micro-PIV using the continuity equation and a comparison of the performance with that of stereoscopic measurements

Recently, a number of techniques have been presented for the determination of the third “out-of-plane” velocity component in micro particle image velocimetry (micro-PIV) data. In particular, the conventional macroscopic stereo-PIV technique has been converted to the micro scale by the use of stereo-microscopy. In this work a different technique is investigated, which uses conventional, two-component micro-PIV to generate velocity data on a number of planes. The in-plane velocity gradients are then calculated, which can be used in the continuity equation to produce the out-of-plane velocity gradients. These, together with the no-penetration boundary condition, can then be used to calculate the out-of-plane velocities. An algorithm is presented that is capable of handling up to one invalid vector per column of data by using a combination of first order and second order projections of the velocity. The advantage of the continuity based technique is that it uses the existing two-component micro-PIV technology, which at present is in a more advanced stage of development then stereo-microscopy based micro-PIV. The technique is investigated using a flow similar to one used previously to assess stereoscopic micro-PIV (Meas Sci Technol 17:2175–2185, 2006). This allows a comparison of the performance of the two techniques. The results show that the continuity based data agrees well with an independent computational fluid dynamics solution and has a smaller experimental uncertainty than the stereoscopic technique at a better spatial resolution. There are, however, potential limitations to the continuity based technique. These include the two-dimensionality of the data, which is limited to the planes on which the original images were taken, and the dependence of the technique on the data close to surfaces, where the experimental errors are often greatest. Stereoscopic micro-PIV does not have these limitations so, whilst at present it appears that continuity based techniques may be more accurate, there is sufficient potential for stereoscopic techniques to justify their further development.