水气两相流中稀疏气泡流动速度场的数字图像测量初探

由空压机提供的气体通过—排微小直径的喷嘴进入静止水体，形成水气两相流流场。在单相PIV和PTV技术的基础上，研究稀疏气液两相流情况下气泡的速度场分布。PIV算法采用快速傅立叶互相关分析法，而PTV算法需要获得每幅图像中每个气泡的形心，根据连续图像中的粒子对，计算速度。用PIV和PTV两种算法处理求出气泡的速度并对两种方法进行比较，其最终研究成果可应用于流体及多相流的流量测技术，提高我们进行低密度气液两相流相关研究的测量水平。同时为水气两相流的数值分析和理论研究提供流场测试的数据。     

风沙两相流测量技术研究进展

围绕风沙两相流的测量, 归纳了过去几十年来在风沙动力学研究中所使用的风速测量技术和输沙率测量装置.着重讨论了高频测量在目前风沙动力学研究中的必要性, 分析了传统风速和输沙率测量装置的优缺点.对新一代光学测量技术------PIV在风沙两相流测量中的应用进行了较为详细的探讨.指出PIV测速技术在风沙两相流研究中具有广泛的应用前景, 使用PIV测速技术可以得到风沙流结构、两相速度场等宏观信息, 同时也可以进行单个颗粒运动状态的研究.      

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。     

两相流显微PIV/PTV系统的开发

开发了一个能同时测量两相流中两相速度和细颗粒尺寸分布的显微PIV/PTV系统,其硬件系统包括大功率连续激光器、显微镜、高速摄像机;软件系统由改进的球形颗粒图像识别算法、各种图像处理算法和各种先进的PIV/PTV算法组成。其中改进的圆弧识别算法能够进行更准确地进行曲线分割而能对充满噪音并相互重叠的颗粒图像给出较好的识别结果。应用该PIV系统,可以在微秒和微米数量级上捕获细颗粒/气泡图像,并能较准确地同时得到两相速度、颗粒尺寸和浓度分布。对焚香可吸入颗粒物进行了速度和尺寸的同时测量,得到了较满意的结果。     

粒子图像测速技术研究进展

粒子图像测速技术(PIV)作为一种全新的无扰、瞬态、全场速度测量方法,在流体力学及空气动力学研究领域具有极高的学术意义和实用价值.本文对PIV技术的原理、分类作了简要地介绍,详细归纳和评述了现有的各种速度信息的提取方法,并对拓扑图论、神经网络、遗传算法、模糊聚类等新技术在PIV中的应用以及三维PIV技术、两相流PIV测试技术进行了介绍.指出当前PIV技术除了向三维和多相流方向发展外,如何提高PIV的测量精度以及缩短计算时间仍然是目前研究的主要目标.PIV技术随着计算机技术、激光技术和CCD性能的发展,必将取得更大的发展与突破      

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...     

风沙两相流跃移层中沙粒相的速度分布

从单个跃移沙粒在气流中的运动方程出发导出了风沙两相流中沙粒相速度分布函数的Boltzmann方程，对风沙流研究中几种不同的分布函数及其相应的统计平均值等基本概念给出了严密的数学定义，指出了不同分布函数之间的区别和联系，在略去铅垂方向空气阻力的情况下，给出了沙粒相速度分布函数沿铅垂方向的边缘分布，作为风沙流中跃移理论的主要基础之一。利用结果对前人在风沙流研究中发现的某些重要规律和现象进行了解释。     

一种改进的高浓度风沙图像的动态灰度阈值分割算法

风沙跃移是塑造干旱区地貌的最主要的动力,其伴生的粉尘的释放、输送和沉降不但严重地影响了大气环境质量,也引起了全球气候系统和海洋系统的变化.单个沙粒轨迹形成是理解粒-床碰撞过程和风沙两相流耦合过程的重要纽带.高浓度风沙图像处理算法是深入理解沙粒轨迹形成机制的关键技术.为了实现对高浓度风沙图像精细处理,本文提出了不依赖于经验参数的动态灰度阈值分割算法,它包括背景模板去噪、绿光通道灰度化处理、图像微分、灰度方差阈值目标检测和最大类间方差灰度阈值分割等,其中背景模板去噪和灰度方差阈值目标检测等是新算法的主要亮点.高浓度风沙图像分割实验显示,扣减背景模板去除了条纹状和斑点状的稳定噪声;图像微分和灰度方差阈值目标检测显著地提高了暗沙粒识别的数量并有效地去除了随机噪声;改进算法的沙粒有效识别个数(人机判读坐标一致的沙粒数目)、查全率(计算机提取沙粒数目与人工判读的实际沙粒数比值)和查准率(有效沙粒数目与实际沙粒数目的比值)分别为461,71%和86%,显著地高于传统算法对应的85,13%和82%,这表明新算法对高浓度风沙图像的分割效果良好.避免单粒子分割和表观重叠问题是进一步完善高浓度风沙图像的分割算法的可能途径.     

一种改进的高浓度风沙图像的动态灰度阈值分割算法

风沙跃移是塑造干旱区地貌的最主要的动力,其伴生的粉尘的释放、输送和沉降不但严重地影响了大气环境质量,也引起了全球气候 系统和海洋系统的变化. 单个沙粒轨迹形成是理解粒--床碰撞过程和风沙两相流耦合过程的重要纽带. 高浓度风沙图像处理算法是深入理解沙粒轨迹形成机制的关键技术. 为了实现对高浓度风沙图像精细处理, 本文提出了不依赖于经验参数的动态灰度阈值分割算法,它包括背景模板去噪、绿光通道灰度化处理、图像微分、灰度方差阈值目标检测和 最大类间方差灰度阈值分割等,其中背景模板去噪和灰度方差阈值目标检测等是新算法的主要亮点. 高浓度风沙图像分割实验显示, 扣减背景模板去除了条纹状和斑点状的稳定噪声;图像微分和灰度方差阈值目标检测显著地提高了暗沙粒识别的数量并有效地去除了随机噪声; 改进算法的沙粒有效识别个数(人 机判读坐标一致的沙粒数目)、查全率(计算机提取沙粒数目与人工判读的实际沙粒数比值)和查准率(有效沙粒数目与实际沙粒数目的比值) 分别为461, 71%和86%,显著地高于传统算法对应的85, 13%和82%,这表明新算法对高浓度风沙图像的分割效果良好. 避免单粒子分割和表观重叠问题是进一步完善高浓度风沙图像的分割算法的可能途径.      

两相流PIV粒子图像处理方法的研究

本文在单相PIV技术的基础上研究了两相流动PIV图像处理方法，采用摸板匹配法和灰度加权标定法对两相粒子进行了识别、区分和标定，采用灰度互相关法对区分后的单相粒子图像进行了处理，应用基于以上方法编制的Windows应用软件，首先对由美国Minnesota大学复杂流动实验室提供的两相流动粒子图片进行了处理，通过对比分析可见，应用本文所采用的方法能对两相粒子进行有效的识别和区分，然后以搅拌槽内液固两相流场为例对此方法进行了应用。     

采用PTV技术研究循环流化床内气固两相流动

采用PTV技术对循环流化床顶部颗粒稀疏流动区域进行了测量，其中采用先进的高速摄像技术获取流动的连续图像，并采用目前有望在气固两相流动测量中发挥较大作用的四种PTV算法：BICC法、VGT法、SPRING法和4-FRAME法，对所获取的图像进行颗粒配对处理，从而得到流场中运动颗粒的速度信息。所得到的结论为：本文所采用的PTV算法在图像处理中都产生少量的伪矢量，通过采取简单的伪矢量识别算法就可以剔除大部分伪矢量；本文实验条件下，测得循环流化床顶部区域内颗粒运动速度差别较小。本文工作为进一步详细实验测量研究奠定了理论与技术基础。     

Measurements of cross-sectional instantaneous phase distribution in gas–liquid pipe flow

Two novel complementing methods that enable experimental study of gas and liquid phases distribution in two-phase pipe flow are considered. The first measuring technique uses a wire-mesh sensor that, in addition to providing data on instantaneous phase distribution in the pipe cross-section, also allows measuring instantaneous propagation velocities of the phase interface. A novel algorithm for processing the wire-mesh sensor data is suggested to determine the instantaneous boundaries of gas–liquid interface. The second method applied here takes advantage of the existence of sharp visible boundaries between the two phases. This optical instrument is based on a borescope that is connected to a digital video camera. Laser light sheet illumination makes it possible to obtain images in the illuminated pipe cross-section only. It is demonstrated that the wire-mesh-derived results based on application of the new algorithm improve the effective spatial resolution of the instrument and are in agreement with those obtained using the borescope. Advantages and limitations of both measuring techniques for the investigations of cross-sectional instantaneous phase distribution in two-phase pipe flows are discussed.     

Simultaneous velocity field measurements in two-phase flows for turbulent mixing of sprays by means of two-phase PIV

This paper describes a novel derivative of the PIV method for measuring the velocity fields of droplets and gas phases simultaneously using fluorescence images rather than Mie scattering images. Two-phase PIV allows the simultaneous and independent velocity field measurement of the liquid phase droplets and ambient gas in the case of two-phase flow mixing. For phase discrimination, each phase is labelled by a different fluorescent dye: the gas phase is seeded with small liquid droplets, tagged by an efficient fluorescent dye while the droplets of the liquid phases are tagged by a different fluorescent dye. For each phase, the wavelength shift of fluorescence is used to separate fluorescence from Mie scattering and to distinguish between the fluorescence of each phase. With the use of two cross-correlation PIV cameras and adequate optical filters, we obtain two double frame images, one for each phase. Thus standard PIV or PTV algorithms are used to obtain the simultaneous and independent velocity fields of the two phases. Because the two-phase PIV technique relies on the ability to produce two simultaneous and independent images of the two phases, the choice of the labelling dyes and of the associated optical filter sets is relevant for the image acquisition. Thus a spectroscopic study has been carried out to choose the optimal fluorescent dyes and the associated optical filters. The method has been evaluated in a simple two-phase flow: droplets of 30–40 μm diameter, produced by an ultrasonic nozzle are injected into a gas coflow seeded with small particles. Some initial results have been obtained which demonstrate the potential of the method.     

Online monitoring of gas–solid two-phase flow using projected CG method in ECT image reconstruction

Electrical capacitance tomography (ECT) is a promising technique for multi-phase flow measurement due to its high speed, low cost and non-intrusive sensing. Image reconstruction for ECT is an inverse problem of finding the permittivity distribution of an object by measuring the electrical capacitances between sets of electrodes placed around its periphery. The conjugate gradient (CG) method is a popular image reconstruction method for ECT, in spite of its low convergence rate. In this paper, an advanced version of the CG method, the projected CG method, is used for image reconstruction of an ECT system. The solution space is projected into the Krylov subspace and the inverse problem is solved by the CG method in a low-dimensional specific subspace. Both static and dynamic experiments were carried out for gas–solid two-phase flows. The flow regimes are identified using the reconstructed images obtained with the projected CG method. The results obtained indicate that the projected CG method improves the quality of reconstructed images and dramatically reduces computation time, as compared to the traditional sensitivity, Landweber, and CG methods. Furthermore, the projected CG method was also used to estimate the important parameters of the pneumatic conveying process, such as the volume concentration, flow velocity and mass flow rate of the solid phase. Therefore, the projected CG method is considered suitable for online gas–solid two-phase flow measurement.     

Void fraction measurement of bubble and slug flow in a small channel using the multivision technique

Using the multivision technique, a new void fraction measurement method was developed for bubble and slug flow in a small channel. The multivision system was developed to obtain images of the two-phase flow in two perpendicular directions. The obtained images were processed—using image segmentation, image subtraction, Canny edge detection, binarization, and hole filling—to extract the phase boundaries and information about the bubble or slug parameters. With the extracted information, a new void fraction measurement model was developed and used to determine the void fraction of the two-phase flow. The proposed method was validated experimentally in horizontal and vertical channels with different inner diameters of 2.1, 2.9, and 4.0 mm. The proposed method of measuring the void fraction has better performance than the methods that use images acquired in only one direction, with a maximum absolute difference between the measured and reference values of less than 6%.     

基于Mask R-CNN网络的磨损颗粒智能识别与应用

针对设备磨损故障诊断中磨粒识别技术难度高、工作主观经验影响大等问题,采用深度学习技术开展了磨粒智能识别的研究,提出了基于Mask R-CNN卷积神经网络的磨粒数字化表征方法. 该方法利用迁移学习训练基于Mask R-CNN网络的磨粒识别模型对图像中磨粒进行识别和实例分割,然后使用Suzuki85算法、迭代算法、等比例计算方法计算出磨粒的真实尺寸,解决了磨粒分析中难定量分析的问题. 结果表明:基于Mask R-CNN网络(采用R-101-FPN骨干网络)训练的磨粒识别模型可以对图像中多个异常磨损颗粒进行识别,综合准确率和召回率达到当前图像识别领域的主流水平. 辅以上述Suzuki85等算法,成功实现磨粒图像的定量评价分析,对促进设备故障诊断技术的自动化发展和工业应用具有一定的实际应用价值.      

Rod-like particles matching algorithm based on SOM neural network in dispersed two-phase flow measurements

A matching algorithm based on self-organizing map (SOM) neural network is proposed for tracking rod-like particles in 2D optical measurements of dispersed two-phase flows. It is verified by both synthetic images of elongated particles mimicking 2D suspension flows and direct numerical simulations-based results of prolate particles dispersed in a turbulent channel flow. Furthermore, the potential benefit of this algorithm is evaluated by applying it to the experimental data of rod-like fibers tracking in wall turbulence. The study of the behavior of elongated particles suspended in turbulent flows has a practical importance and covers a wide range of applications in engineering and science. In experimental approach, particle tracking velocimetry of the dispersed phase has a key role together with particle image velocimetry of the carrier phase to obtain the velocities of both phases. The essential parts of particle tracking are to identify and match corresponding particles correctly in consecutive images. The present study is focused on the development of an algorithm for pairing non-spherical particles that have one major symmetry axis. The novel idea in the algorithm is to take the orientation of the particles into account for matching in addition to their positions. The method used is based on the SOM neural network that finds the most likely matching link in images on the basis of feature extraction and clustering. The fundamental concept is finding corresponding particles in the images with the nearest characteristics: position and orientation. The most effective aspect of this two-frame matching algorithm is that it does not require any preliminary knowledge of neither the flow field nor the particle behavior. Furthermore, using one additional characteristic of the non-spherical particles, namely their orientation, in addition to its coordinate vector, the pairing is improved both for more reliable matching at higher concentrations of dispersed particles and for higher robustness against loss of particle pairs between image frames.