互相关法在管道雨水流速测量中的应用研究

针对雨水管道中流体成分的多样性和流动型态的复杂性,借鉴粒子图像测速中的流场测量思想,提出了一种基于互相关分析的管道雨水流速测量方法;传统的互相关方法计算量很大,文章对互相关分析的快速算法进行了研究,并将FFTW快速傅里叶变换算法库应用于测量软件的实现中;使用堰槽建立了管道雨水流速标定装置,在不同的流速下对该方法进行了实验验证;实验证明,利用速度场提取平均速度的方法很好地平滑了管道中流体流动的复杂多变性,相对测量误差在6％以内,能够比较准确地测量出雨水的平均流速,可有效应用于实际测量.     

河流水面成像测速方法的比测试验研究

大尺度粒子图像测速(LSPIV)是一种新兴的非接触式瞬时全场流速测量技术。以LSPIV为基本原理,针对现场条件下特有的水流示踪物、复杂的光学成像环境及受限的测点布设方式,通过对流场图像采集、水面背景抑制、运动矢量估计、时均流场重建、水面流场定标及断面流量估计等技术方法的集成创新,建立一套完整的河流水面成像测速(RSIV)工作模式。为评价RSIV的性能并提出研究需求,在现场开展与流速仪法和雷达法的比测试验。结果表明,RSIV法的时均流速测量精度可以达到0.5 mm/s以内,相比流速仪法具有更高的时空分辨率。当流速系数和断面划分方式选择合适时,流量估计值和雷达法的一致性较好。试验初步验证河流水面成像测速方法用于河流流速、流量测量的可行性。     

在线式DPIV系统的开发与应用

介绍了一种自行研制的在线式数字粒子图像测速系统,首先说明这种系统的主要特点,然后从系统的硬件组成和软件结构两个方面进行了介绍.该系统的软件部分是整个系统的研究重点,包括图像采集模块,自相关图像分析模块、互相关图像分析模块以及数据后处理模块等.为了验证该系统的有效性,设计了水流流场分布的测量实验,实验结果表明系统能够提取出合理的水流流场速度分布.最后,利用该系统分析内燃机缸内流场的PIV图像,得到了内燃机缸内流场的流速分布.     

基于FPGA的固体测速系统的设计与应用

针对目前工业生产过程中的固体流速测量问题,提出了一种基于 FPGA的固体流速测量系统。该系统以相关测速算法为理论基础,通过发射载波信号到测试管道,并采集管道内两个不同位置的流速信号,对这两路信号进互相关运算,寻找峰值点,从而间接求得固体流速。该系统包括一套基于 FPGA的硬件系统和一套基于 C++的上位机软件系统。经过测试验证,本系统实现了固体流速的精确测量,性能稳定,达到了设计目标要求。     

粒子测速系统中相位相关法在的优化设计

介绍了相位相关法的匹配原理。针对在粒子测速系统(PIV)应用中由于粒子运动而引起的不匹配以及亚像素快速求解等问题,提出了分层匹配后“伪粒子”的去除方法和相关运算的快速求解算法。使用优化的匹配流程仅需一次2D-FFT便可准确求出两幅粒子图像的亚像素级匹配点。最后,使用合成的粒子图像进行了算法验证和效率分析并给出了仿真结果。经验证,优化后的相位相关匹配具有高效性与可靠性。     

粒子测速系统中刚性平移运动假设条件

在对流场进行的粒子示踪测量中,针对空间运动粒子透视成像后易出现的误匹配问题,研究了粒子图像测速技术中近邻粒子平移运动假设,提出了三点式结构约束.该约束条件基于粒子图像测速技术的近邻性匹配准则和机器视觉映射原理,利用视平面内相同运动的特征平面共线的性质,对前后2帧图像中的粒子进行运动检测.最后通过仿真实验证明了该约束条件的有效性.     

PIV应用于气液两相流的研究现状

作为一种全新的无扰、瞬态、全场速度测量技术,粒子图像测速(PIV)技术近年来在单相流和多相流领域得到了广泛的应用.对于气液两相流PIV技术,目前还处于起步与发展阶段.着重概述了两相示踪粒子的采样技术,并对近年来国外PIV技术在气液两相流动领域中的研究现状做了总结与分析,指出PIV技术在气液两相流体特性研究中具有很好的应用前景.     

基于密度聚类分析的粒子测速算法

提出了一种具有密度预测分析的粒子图像测速算法(Density clustering particle image velocimetry,DCPIV).在对粒子图像进行预处理时,根据图像中粒子分布的复杂性以及流体运动的连续性,首先使用密度聚类法对粒子图像按密度进行划分,然后对不同区域的密度图进行相关处理,并将此结果作为粒子相关或者粒子追踪的预测值进行处理.最后,使用合成的粒子图像进行了方法验证,结果表明:该方法能够解决实际操作时粒子分布不匀的问题以及由于旋转所引起的误匹配问题,并且处理结果具有较高的精度.     

PIV软件IMPACT的研制与应用

开发了一套面向对象的PIV图像处理软件——IMPACT。该软件内嵌多种先进的数据处理与分析算法。对不同数据处理算法进行了检验，结果表明：该PIV系统可有效获得流体流动的图像并可准确进行数据处理，完全可用于实际流体流动的测量。     

应用PSO与GA混合算法重建超分辨图像

结合粒子群优化算法和遗传算法中的交叉与选择操作,提出了一种混合算法,对提出的混合算法用两个具有多个局部极值的函数进行了测试,测试结果表明混合算法寻优能力优于粒子群优化算法;利用该混合算法对低分辨率图像序列重建出一幅高分辨率图像。实验结果表明,该方法重建图像的视觉效果和信噪比均优于遗传算法与梯度下降算子相结合的混合算法重建图像的效果。     

Experimental and numerical investigation of unsteady cavitating flows through a 2D hydrofoil

In the present study, firstly, the unsteady cavitating flows around a hydrofoil are studied based on the flow visualization and detail velocity measurement, a high-speed video camera is used to visualize the flow structures, and a particle image velocimetry (PIV) technique is applied to the measurement of the time-averaged and instantaneous velocity and vorticity fields. The results show that the unsteadiness of mass transfer process between the vapor and the two-phase regions is substantial, a self-oscilla...     

Optical measurement of pore scale velocity field inside microporous media

An experimental technique to quantify velocity field at pore scale with in microporous media, formed by packing of microglass spheres of size 200?μm inside a glass micro-model, is presented. A microparticle image velocimetry (μ-PIV) system is used to study velocity fields at four different spatial regions in the microporous medium. A combined particle image velocimetry (PIV) and particle tracking velocimetry (PTV) scheme is used to quantify velocity within a typical pore size of 10–50?μm. The experiments are conducted at four different flow rates. Two different measurement planes are selected for obtaining the detailed pore scale velocity field—one close to the glass wall and the other inside the porous medium at a distance 100?μm below the glass wall. The image processing technique for dealing with noisy data and sparse vector field has been discussed in detail. Probability density functions of transverse and axial velocity components are compared with available results in literature. The pore scale velocity field obtained can provide insight to flow properties in microporous media and can be a powerful tool to validate existing numerical results for flow through porous media.     

Visualization of flashback in a premixed burner with swirling flow

In this study,the measurement object is a flame propagating in a premixed burner with swirling flow in order to investigate unsteady flame behavior in a gas turbine premixer.During flashback,the flame propagating upstream was visualized with a high-speed camera.Moreover,we established the technique to measure the instantaneous flow fields of unburned fuel-air mixture in a swirling premixed burner using particle image velocimetry(PIV).As a result,the characteristics of flame behavior propagating upstream wer...     

Multispectral processing for color particle image velocimetry

Since the adoption of digital video cameras and cross-correlation methods for particle image velocimetry (PIV), the use of color images has largely been abandoned. Recently, however, with the re-emergence of color-based stereo and volumetric techniques, and the extensive use of color microscopy, color imaging for PIV has again become relevant. In this work, we explore the potential advantages of color PIV processing by developing and proposing new methods for handling multi-color images. The first method uses cross-correlation of every color channel independently to build a color vector cross-correlation plane. The vector cross-correlation can then be searched for one or more peaks corresponding to either the average displacement of several flow components using a color ensemble operation, or for the individual motion of colored particles, each with a different behavior. In the latter case, linear unmixing is used on the correlation plane to separate each known particle type as captured by the different color channels. The second method introduces the use of quaternions to encode the color data, and the cross-correlation is carried out simultaneously on all colors. The resulting correlation plane can be searched either for a single peak, corresponding to the mean flow or for multiple peaks, with velocity phase separation to determine which velocity corresponds to which particle type. Each of these methods was tested using synthetic images simulating the color recording of noisy particle fields both with and without the use of a Bayer filter and demosaicing operation. It was determined that for single-phase flow, both color methods decreased random errors by approximately a factor of two due to the noise signal being uncorrelated between color channels, while maintaining similar bias errors as compared to traditional monochrome PIV processing. In multi-component flows, the color vector correlation technique was able to successfully resolve displacements of two distinct yet coupled flow components with errors similar to traditional grayscale PIV processing of a single phase. It should be noted that traditional PIV processing is bound to fail entirely under such processing conditions. In contrast, the quaternion methods frequently failed to properly identify the correct velocity and phase and showed significant cross talk in the measurements between particle types. Finally, the color vector method was applied to experimental color images of a microchannel designed for contactless dielectrophoresis particle separation, and good results were obtained for both instantaneous and ensemble PIV processing. However, in both the synthetic color images that were generated using a Bayer filter and the experimental data, a significant peak-locking effect with a period of two pixels was observed. This effect is attributed to the inherent architecture of the Bayer filter. In order to mitigate this detrimental artifact, it is suggested that improved image interpolation or demosaicing algorithms tuned for use in PIV be developed and applied on the color images before processing, or that cameras that do not use a Bayer filter and therefore do not require a demosaicing algorithm be used for color PIV.     

Velocity measurement in microchannels with a laser confocal microscope and particle linear image velocimetry

Particle linear image velocimetry (PLIV), a novel velocity measurement method for microfluidic characterization, is reported. The method records a series of one-dimensional images that represent the trace of particles in the flow across a one-dimensional imager. Linear imaging results in a faster frame rate than planar imaging, allowing observations at larger magnifications, or the measurement of faster flow in real-time than comparable techniques. In contrast to particle image velocimetry (PIV), PLIV captures fast flow dynamics and does not require high-speed cameras or shutters. Furthermore, PLIV is adaptable to multiple linear imager formats and, as one example, can use laser scanning confocal microscopes (LSCMs) that acquire images slowly, but with high optical sectioning resolutions. A higher spatial resolution can be obtained for flows where the in-plane velocity gradient in the direction of the optical path (z direction) is important. The PLIV algorithm is fully described and its utility is demonstrated by the measurement of: a steady Poiseuille flow with 1-m spatial resolution in a microfluidic environment; dynamic measurement of transient flows with 250-ms temporal resolution; and the simultaneous calculation of particle dimension statistics.     

Measurement of periodic micro flows using micro-particle image velocimetry with phase sampling

A phase-sampling method has been developed to measure periodic flows at a high temporal resolution using conventional micro-particle image velocimetry (PIV). In this technique, the sampling is set such that each velocimetry dataset represents a unique point in phase of a periodic flow. The flow characteristics over a single cycle are reconstructed from measurements over a number of cycles, thus allowing measurement at a higher temporal resolution than the PIV system. The flow measurements were performed for AC electroosmotic flows and verified with results from the phase-locking technique. The temporal resolution is limited by the shortest camera exposure time and the time separation between laser pulses. The theoretical sampling resolution can be as low as 20 μs for 100 Hz periodic flows. A resolution of 200 μs was obtained in the experiment using 40 velocimetry datasets.     

Crowd-based velocimetry for surface flows

Flow velocity measurement is important in hydrology. Recently, owing to the popularity of sensors and processors, image-based flow velocity measurement methods have become an important research direction. Particle image velocimetry (PIV) is a key example. However, due to the uncertainty of the features, PIV sometimes provides very inaccurate results and always requires customized setups. In this research, we take advantage of the human perception system, that is, the strong abilities related to feature identification and tracking, in order to estimate the surface flow velocity of a river. We developed a method called crowd-based velocimetry (CBV) to incorporate the human perception capacity in the estimation of the flow velocity. CBV includes three main steps: (1) video processing, (2) crowd processing, and (3) statistical processing. We validated CBV by measuring a fast, steady, and uniform river surface flow in an artificial canal. The results show that compared to radar measurements from the center of the flow, CBV measured the surface flow velocity with a deviation ranging between +12.1% and +17.3% from the radar measurement, while PIV resulted in a −1.7% to −24.3% deviation. With rapidly improving mobile devices, CBV allows enormous numbers of people to engage in flow measurement, making CBV more reliable, more efficient, and more economical.     

PIV measurement on internal instantaneous flows of a centrifugal pump

In this paper,the internal flow field in a centrifugal pump working at the design flow rate operating condition has been measured using the particle image velocimetry(PIV)technique with the fluorescent particles and the index-matched fluid technology.The index-marching fluid with the same refractive index as the transparent material has been prepared and applied in the present test of pump with geometrical complex walls.The comparison between velocity distributions of PIV results both with and without fluor...     

Combined measurement of concentration distribution and velocity field of two components in a micromixing process

A lot of production processes involve mixing steps. The understanding of fluid flows in mixing processes of liquid components is needed in order to develop appropriate mixers for the chemical and pharmaceutical industry. Especially mixing in microfluidic systems is a challenge due to the diffusion-based processes. A multi-lamination micromixer with chessboard outlet geometry is used to induce the mixing process. To get comprehensive information about the mixing process, the velocity profile of the fluid flow and the species concentration distribution during the mixing process should be measured. Thus, we have combined particle image velocimetry (PIV) and Raman scattering. To enable rapid detection, the Raman imaging mode is used to visualise the concentration distribution. By this setup light sheets along and orthogonal to the outlet of the micromixer are recorded and synchronized with PIV measurement. As a model system we have used water and ethanol/methanol, enabling a selective monitoring of the substances by choosing appropriate spectral areas. The PIV is recorded based on Mie scattering and fluorescence using microsphere tracers. In this study, we present a setup for determination of the velocity profile field and the spatial concentration distribution of water and ethanol/methanol in a micromixer.     

本征正交分解在数据处理中的应用及展望

本征正交分解(Proper Orthogonal Decomposition,POD)是对高维复杂非线性系统进行降维处理的有效方法之一.本文对POD方法在一系列实际工程领域降维中的研究进行了综述.首先简要介绍POD方法的发展历史,简述POD方法分类,随后详细列举POD方法在粒子图像测速(Particle Image Velocimetry,PIV)技术、计算流体力学(Computational Fluid Dynamics,CFD)数据处理中的应用.对比了POD方法和动态模态分解(Dynamic Mode Decomposition,DMD)方法在实际工程应用中各自的优缺点,结果表明在流场稳定脉动时可采用DMD方法,而其他随时间变化的流场采用POD方法更合适.最后对POD方法的发展尤其是在人工智能领域的应用做出展望.