A modified cross-correlation algorithm for PIV image processing of particle-fluid two-phase flow

PIV (Particle Image Velocimetry) technique for flow field measurement has achieved popular self-identify through over ten years development, and its application range is becoming wider and wider. PIV post-processing techniques have a great influence on the success of particle-fluid two-phase flow field measurement and thus become a hot and difficult topic. In the present study, a Phase Respective Identification Algorithm (PRIA) is introduced to separate low-density solid particles or bubbles and high-density tracer particles from the PIV image of particle-fluid two-phase flow. PTV (Particle Tracking Velocimetry) technique is employed to calculate the velocity fields of low-density solid particles or bubbles. For the velocity fields of high-density solid particles or bubble phase and continuous phase traced by high-density smaller particles, based on the thought of wavelet transform and multi-resolution analysis and the theory of cross-correlation of image, a delaminated processing algorithm (MCCWM) is presented to conquer the limitation of conventional Fourier transform. The algorithm is firstly testified on synthetic two-phase flows, such as uniform steady flow, shearing flow and rotating flow, and the computational results from the simulated particle images are in reasonable agreement with the given simulated data. The algorithm is then applied to images of actual bubble-liquid two-phase flow and jet flow, and the results also confirmed that the algorithm proposed in the present study has good performance and reliability for post-processing PIV images of particle-fluid two-phase flow.     

Optimization in PIV algorithm for visualizing vortices in bubble wake

The PIV (Particle image velocimetry) is the most commonly used method for flow field observation because of its high efficiency and non-interference to the flow field. This study aims to clarify the optimal parameter conditions used in the cross-correlation algorithm of PIV for flow fields with vortices. The influence factors on the error of the cross-correlation algorithm are analyzed and discussed using a synthetic flow field, including the seeding conditions, the velocity gradient and vortex size. It is confirmed that the minimum particle number density per interrogation window is about 10, which generally limits the minimum size of the window. For a vortex, when the vortex size is fixed, the velocity gradient corresponding to the characteristic velocity both controls the lower and upper limitation of window size. For a relatively small vortex, generally a window not larger than the vortex size is asked. Then, a strategy to improve the observation based on the existing equipment is discussed and applied to visualize a rising bubble wake based on LIF (Laser-induced fluorescence) images.     

粒子图像测速（PIV）技术在烟丝流量检测中的研究

粒子图像测速技术（PIV）是一种全新的非接触式的,瞬时的,全场流速测量方法,广泛应用于流体力学中。本研究将PIV技术引入烟丝运动研究是一个尝试,旨在为烟丝流量的检测提供一个新的测量手段。通过分析烟丝在风送管道内的运动,利用PIV技术并结合PTV技术,采用图像处理得到烟丝的运动速度。粒子图像测速技术具有一定的优势,可以克服传统测量手段的不足。     

基于PIV测量的涡轮流量计响应分析

应用粒子成像测速技术获得了涡轮流量计叶片入口流场的速度分布信息,并基于该测量结果,运用T-G模型理论得出流量计的响应.通过与以往所采用的几种典型的入口速度分布计算得到的结果比较分析表明,基于PIV测量的结果更接近于涡轮流量计的真实响应.还比较分析了涡轮入口速度分布对涡轮流量计响应的影响机理,相关结果可望为改进涡轮流量计响应的计算分析方法以及优化设计提供有价值的参考.     

改进的光流运动图像分析方法及其应用

针对传统光流运动图像分析方法运动估计精度低且易受各种干扰等缺点,提出一种基于梯度阈值的五置信点约束的改进光流算法.该方法采用五置信点加权法处理像素时间和空间梯度值,减小了单个像素受噪声的影响.对基本光流约束方程进行了梯度阈值处理,剔除了光流场中不利于运动估计的干扰数据,提高了运动图像的运动估计精度.实验分别采用传统算法...     

基于运动显著图和光流矢量分析的目标分割算法

为提高运动目标分割算法对多种复杂场景的自适应能力和分割精度,提出一种基于运动显著图和光流矢量分析的目标分割算法。该算法首先基于运动显著图提取运动目标的大致区域,然后利用光流矢量获得运动目标和背景区域的运动边界,并结合点在多边形内部原理得到运动目标内部精确的像素点,最后以超像素为基本分割单元,通过引入置信度的概念实现最终像素一级的目标分割。通过与典型算法进行多场景实验对比,表明该算法能够有效实现多种复杂场景下的运动目标分割,并且较现有算法具有更高的分割精度。     

Evaluation of recursive PIV algorithm with correlation based correction method using various flow images

The hierarchical recursive local-correlation PIV algorithm with CBC (correlation based correction) method was employed to increase the spatial resolution of PIV results and to reduce error vectors. The performance of this new PIV algorithm was tested using synthetic images, PIV standard images of Visualization Society of Japan, real flows including ventilation flow inside a vehicle passenger compartment and wake behind a circular cylinder with riblet surface. As a result, most spurious vectors were suppressed by employing the CBC method, the hierarchical recursive correlation algorithm improved the sub-pixel accuracy of PIV results by decreasing the interrogation window size and increased spatial resolution significantly. However, with recursively decreasing of interrogation window size, the SNR (signal-to-noise ratio) in the correlation plane was decreased and number of spurious vectors was increased. Therefore, compromised determination of optimal interrogation window size is required for given flow images, the performance of recursive algorithm is also discussed from a viewpoint of recovery ratio and error ratio in the paper.     

磁力搅拌湍流场的PIV测量及流场演变的POD分析

为了解磁力搅拌过程湍流特性,对其开展了激光粒子图像测速(PIV)试验,并进行了本征正交分解(POD)分析.分析表明,在测量平面转子外部区域,除平均流动,含能量较高的流动结构为循环剪切流和转子旋转的尾涡结构.在搅拌槽底部具有较高的旋涡强度,有利于固体颗粒悬浮.流体与转子之间的流-固耦合作用使转子产生振荡,随转速升高,系统...     

基于MATLAB的PIV软件(MPIV)的开发与应用

研究一种基于MATLAB的PIV软件MPIV，可处理各种粒子密度的PIV图像。选用两种有代表性的算法，分别是对应于高粒子密度图像的基于快速傅立叶变换的互相关法，以及对应于低粒子密度图像的二值化图像相关法，以旋转流场为例，通过计算机模拟粒子图像，检验软件的可行性。     

基于图像处理的光纤预警系统模式识别

针对相位敏感光时域反射计(Φ-OTDR)光纤预警系统对一维信号进行模式识别产生的误报和较低的识别效率,提出基于形态学方法提取时空二维信号特征,并利用相关向量机(RVM)分类器对事件进行分类识别的方法。首先,将Φ-OTDR采集到的时空二维信号当作图像,根据信号在图像上的特征采用图像处理的方法对不同入侵事件信号进行阈值分割。然后,基于本文提出的特征提取方法,利用不同事件区域在幅值、面积、形状以及区域间隔上的差别提取不同信号特征。最后,利用相关向量机分类器对不同事件信号进行识别并采用"一对一"的多分类策略。对3种管道安全事件进行了实验。实验结果表明,本文提出方法的识别精度能够达到97.8%,而算法时间不到1s。与传统模式识别方法相比,提出的算法大幅度地改善了系统性能,且简便易行,能够满足Φ-OTDR光纤预警系统在线实时监测的要求。     

光学相干层析医学图像处理及其应用

由于人工分析光学相干层析（OCT）图像费时费力、主观及可重复性差,因而快速、精确与客观地检测与量化生物特征标记是OCT医学图像研究与疾病诊断的关键。本文综述了光学相干层析（OCT）医学图像处理技术与应用的研究进展。介绍了OCT成像技术的特点及其主要应用,OCT图像处理的难点、基本问题及主要研究内容;讨论了对时域OCT和频域OCT图像降噪、图像分类与图像分割的重要方法及应用,并分析了各种方法的优缺点及研究发展方向。此外,介绍了偏振敏感光学相干层析（PS-OCT）在医学图像分析中的应用。文中讨论的应用对象涉及到视网膜、角膜、冠脉、前列腺、牙齿、食道、结肠、膀胱、皮肤、乳腺等组织,可为人们综合了解OCT图像处理及其应用现状提供丰富的信息。     

River velocity measurements using optical flow algorithm and unoccupied aerial vehicles: A case study

Accurate and reliable measurements of river flow are critical for a multitude of hydrologic engineering applications. However, flow rate measurements using in-situ sensors are uncertain in many applications and physical measurements of velocity may not be practical due to inaccessible sites or flood conditions. Recent advances in remote sensing using unoccupied aerial vehicles have overcome these limitations through non-contact measurements of river velocities; however, existing approaches have several shortcomings, including the need for artificial tracers in the absence of debris and prior knowledge of tracer size, shape, and flow direction. This case study seeks to overcome these shortcomings through the development of a system that utilizes drones, video imaging, and state-of-the-art optical flow algorithms to measure velocity in rivers. This system was applied along Menomonee River in Wauwatosa, WI. To remotely sense river flow, a DJI Matrice 210 RTK drone equipped with a Zenmuse X5S camera was used to capture video. The video data from the drone was analyzed using optical flow algorithms to generate velocity estimations. River velocity was measured directly at point locations using a hand-held velocimeter. Results indicate that the optical flow algorithms estimate the magnitude of surface velocity to within 13–27% of hand-held measurements without the use of artificial seeding. These outcomes suggest that this system could be used as a possible method to measure velocities in rivers.     

光流法运动估计在FPGA上的实现与性能分析

图像序列的光流估计理论在机器视觉领域已被提出多年,但算法的高计算复杂度限制了其在工业领域的应用。为了满足应用的实时性要求,阐述了一种光流实时估计的实现方法。为了提高算法精度及减少FPGA片内资源消耗,对L&K光流计算方法进行改进。首先,通过设计两层光流计算架构来提高精度。针对在此过程中出现的外部存储器读写速率不够的问题,提出一次读取同时分层缓存、分时计算的方法。考虑到两层光流在计算过程中的迭代关联性,设计了满足要求的外部存储器数据读出顺序表;然后,针对卷积运算资源消耗大的问题,设计了新的卷积权重函数,能够将卷积计算量降低73%,从而节省了大量逻辑资源;最后通过实验验证,所提出的FPGA光流计算方法的精度高于运行在PC平台的L&K方法,卷积计算资源消耗明显降低。设计的系统可以完成1280×1024 pixel、60 frame/s输入视频的计算,满足光流计算的实时性要求。     

A hybrid phase boundary detection technique for two-phase-flow PIV measurements

Particle Image Velocimetry (PIV) measurement accuracy is lower along the phase boundaries of two-phase-flows, because the interrogation windows contain information from both phases. Different seeding density, background intensity, velocity magnitude and flow direction conditions often exist across the boundary, and the cross-correlation-based PIV algorithm selects only the highest correlation peak. The highest correlation peak is either influenced by the wrong phase (across the boundary), or the correctly calculated displacement is erroneously detected as an outlier at a later stage and is subsequently replaced. Phase-separated PIV measurements minimize this problem, and increase accuracy along the boundary by treating each phase separately. This type of measurement requires for each time step; (i) the accurate detection of the phase boundary in consecutive frames, (ii) generation of dynamic phase masks, (iii) an accurate PIV evaluation of each phase and (iv) recombination of the flow fields. In this article, we focus on the first step and test a hybrid phase boundary detection (PBD) technique in three different two-phase-flow configurations which manifest different challenges: The first configuration is the mixing of two liquids in a magnetic micromixer, the second is a combustion experiment where a turbulent, pre-mixed, low-swirl, lifted flame is investigated, and the third is a bubble column reactor where air bubbles are rising in a water tank. The PBD implementation uses a three-step procedure: approximate global thresholding, local Otsu thresholding, and discrimination of image gradients. Comparison of results with and without the use of PBD and phase separation indicate that there are significant measurement accuracy improvements along the boundary.     

基于光流模型的图像运动估计方法

运动图像序列参数估计是电子稳像的关键技术之一.安装在运动载体上的摄像机采集图像时,由于载体姿态变化产生不平稳运动,这种不平稳运动将影响摄像系统的成像质量.电子稳像的目的就是通过计算运动参数并校正图像,以保证处理后的图像序列达到稳定效果.光流模型是处理运动图像的有效方法,本文介绍了用光流模型计算运动图像参数的基本原理和步骤.根据图像像素强度守恒原理,建立光流约束方程,计算运动参数,最后结合实例计算两帧样本图像之间水平和垂直位移量,并绘制光流矢量图.     

Particle image velocimetry investigations on multiphase flow in fluidized beds: A review

Fluidized Beds (FBs) are widely employed in the petroleum and coal energy sector because they offer excellent contact, both in terms of high surface area and long times. The last two decades has seen measurement on multiphase flows shift from conventional pressure sensors to direct flow image acquisition and processing. Particle Image Velocimetry or PIV, and PIV coupled with Digital Image Analysis or DIA, are used to directly and instantaneously acquire flow field data to make hidden flow patterns and flow structures discoverable. Research abounds on Gas-Solid FB hydrodynamics using PIV, but Liquid-Solid and Gas-Liquid-Solid systems are only slowly catching up. Similarly, the use of Geldart B and D particles for such studies is very common, whereas A and C type particle hydrodynamics is as yet largely unexplored by using imaging. Turbulence, high temperature, particle clusters, particle agglomeration and dense particle flows pose particular challenges to using PIV in FB. The two-zone FB and micro-FB warrant further attention. Small sized A & C type particles of rod-like, plate-like and angular shape provide huge scope for PIV investigations on FBs in the future. This review provides a concise account of several PIV studies on all types of FBs with focus on the past two decades, and also details the limitations of PIV measurements with future scope of work.     

Experimental PIV and LIF characterization of a bubble column flow

Experimental 2D Particle Image Velocimetry (PIV) measurements, with uniform background lighting and Laser Induced Fluorescence (LIF) of the tracking particles, were performed in order to characterize the air-water biphasic flow and the 2D bubble column rising velocity in static water. Some applications require knowledge of the simultaneity of two-phase flow characteristics. The two phase flow air/water are common application in industry as chemical, hydraulic and nuclear industry, water treatment by aeration, and measurements are implemented to characterize the behaviour of the air bubbles column flow. The bubble flow studied in this paper is related to the optimization of the aeration in hydraulic turbines with micro-bubbles. The first step of this study, presented in the paper, is a complete characterization of a bubble column issued from a metallic sparger with holes of 0.5 mm diameter. For its complete characterization is determined simultaneously, via image processing technics, the flow velocity field induced by the column of bubbles in water, and the bubbles features: the bubble ascension velocity, diameter variation, interfacial area and shape factor. The results are compared with bibliographical data.     

桑色素-Al掺杂的溶胶-凝胶薄膜修饰的MPOF光纤氟离子传感探头

本文通过对微结构聚合物光纤修饰桑色素-铝配合物掺杂的凝胶薄膜,制备了一种氟化物光纤传感探头。这种探头的结构基于微结构聚合物光纤实现,其内部具有贯穿的微孔道结构,这种微孔结构可以作为敏感材料的载体以及微传感池。敏感层的修饰通过溶胶-凝胶过程实现,将掺有桑色素-铝的溶胶直接吸入光纤内部,可以在光纤微孔阵列中形成凝胶敏感膜。微结构光纤内部可以容纳微量液体,传感过程在微孔道内进行。传感原理基于荧光淬灭远离实现,氟离子对凝胶膜中桑色素-铝具有强烈的荧光淬灭作用,因此传感探头对于不同浓度的氟离子溶液表现不同的荧光强度。在pH值为4.6的条件下,探头对于氟离子具有良好的响应,其传感范围为5-50mmol/L。