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。     

Background extraction from double-frame PIV images

This study presents a simple image pre-processing scheme to extract background information from double-frame particle image velocimetry (PIV) images. Everything that stays stagnant in the image (e.g., image background and light reflections from stationary objects) is assumed to be a source of disturbance and is removed by subtracting the second frame of the image pair from the first frame. This yields a single frame difference image, which is transferred back to a background extracted double-frame image. After the procedure the background in the image does not correlate with itself anymore and therefore a bias error in PIV analysis towards zero displacement is avoided. The simulations show that the procedure conserves the profile of tracer particle images when a displacement between the frames is larger than a particle image size. The performance of this procedure is emphasized with various examples, and extensions of the procedure are introduced. The extended procedure extracts background objects that move between the image frames, e.g. dispersed phase particles in a two-phase flow or laser light sheet reflections from moving objects.     

Limits on the resolution of correlation PIV iterative methods. Practical implementation and design of weighting functions

Elsewhere in this volume (Nogueira et al. (2005) Exp Fluids, in press), the conceptual background that explains the possibility of resolving wavelengths smaller than the size of the interrogation window, with no basic restrictions but sampling, has been explained. Here, a practical implementation of the concepts is performed. To achieve this resolution in iterative PIV processing, an appropriate weighting function can be used, as commented in that reference. Here, the constraints for the design of such weighting functions are presented and analysed. This opens a line of work on possible weighting functions to develop, since the weightings used in these iterative methods, like local field correction particle image velocimetry (LFC-PIV) (Nogueira et al. (1999) Exp Fluids 27(2):107–116), have not been optimised yet. As an example, different weighting functions are commented and tested both on synthetic and real images. The results on these new weightings indicate that the current ones can be improved and the optimisation criteria are open for further advancement.     

Non-intrusive temperature measurement using microscale visualization techniques

μPIV is a widely accepted tool for making accurate measurements in microscale flows. The particles that are used to seed the flow, due to their small size, undergo Brownian motion which adds a random noise component to the measurements. Brownian motion introduces an undesirable error in the velocity measurements, but also contains valuable temperature information. A PIV algorithm which detects both the location and broadening of the correlation peak can measure velocity as well as temperature simultaneously using the same set of images. The approach presented in this work eliminates the use of the calibration constant used in the literature (Hohreiter et al. in Meas Sci Technol 13(7):1072–1078, 2002), making the method system-independent, and reducing the uncertainty involved in the technique. The temperature in a stationary fluid was experimentally measured using this technique and compared to that obtained using the particle tracking thermometry method and a novel method, low image density PIV. The method of cross-correlation PIV was modified to measure the temperature of a moving fluid. A standard epi-fluorescence μPIV system was used for all the measurements. The experiments were conducted using spherical fluorescent polystyrene-latex particles suspended in water. Temperatures ranging from 20 to 80°C were measured. This method allows simultaneous non-intrusive temperature and velocity measurements in integrated cooling systems and lab-on-a-chip devices.     

Development of fiberscope PIV system by controlling diode laser illumination

Because of the inherent small size of optical fiberscopes, they provide access and relative handling ease in given closed vessels, which are hardly equipped with extra windows for conventional flow visualization. The use of an optical fiberscope in conjunction with a conventional particle image velocimetry/particle tracking velocimetry (PIV/PTV) system without optimization can lead to degraded transmission of images. The present study proposes a processing technique to filter background noise contained within the coarse bundle image by subtracting the original image of the bundle as reference image. Additionally, efforts were made to increase the reliability of vector processing using particle streak images via judicious pulse interval and duration adjustments. As an applications test we measured classic jet flow using the developed system and using established conventional measurement techniques. Our tests confirmed that our fiberscope PTV system provides vector fields with sufficient accuracy.     

An extension of digital PIV-processing to double-exposed images

 In this paper digital processing techniques for PIV (Partical Image Velocimetry) using double-exposed particle images have been studied. It has been found that a pattern matching technique is significantly superior to the traditional autocorrelation method in the case that a large particle displacement between the double exposures is present on the image. In PIV using double-exposed images, the image shifting technique is usually used to solve the directional ambiguity problem. The performance of PIV using autocorrelation technique is dependent on the flow speed and the amount of image shift applied. This dependence, for example, causes a difficulty of autocorrelation in flows close to a solid boundary. The present study shows that a pattern matching technique eliminates such a difficulty. At the same signal-to-noise ratio, the pattern matching techndique has a better spatial resolution than that of autocorrelation. In concert with the pattern matching technique, PID (Particle Image Distortion) can be applied to double-exposed images, further improving the reliability and accuracy of velocity estimates of PIV in the presence of large velocity gradients. Generally speaking, PIP-matching and PID extend the validity of PIV using double-exposed images. The total processing time required by the PIV using the pattern matching technique and one PID iteration is of the same order as that required by the PIV using autocorrelation. Received: 7 July 1995 / Accepted: 11 September 1997     

Simultaneous planar measurement of droplet velocity and size with gas phase velocities in a spray by combined ILIDS and PIV techniques

A new approach for simultaneous planar measurement of droplet velocity and size with gas phase velocities is reported, which combines the out-of-focus imaging technique ‘Interferometric Laser Imaging Droplet Sizing’ (ILIDS) for planar simultaneous droplet size and velocity measurements with the in-focus technique ‘Particle Image Velocimetry’ (PIV) for gas velocity measurements in the vicinity of individual droplets. Discrimination between the gas phase seeding and the droplets is achieved in the PIV images by removing the glare points of focused droplet images, using the droplet position obtained through ILIDS processing. Combination of the two optical arrangements can result in a discrepancy in the location of the centre of a droplet, when imaging through ILIDS and PIV techniques, of up to about 1 mm, which may lead to erroneous identification of the glare points from droplets on the PIV images. The magnitude of the discrepancy is a function of position of the droplet’s image on the CCD array and the degree of defocus, but almost independent of droplet size. Specifically, it varies approximately linearly across the image along the direction corresponding to the direction of propagation of the laser sheet for a given defocus setting in ILIDS. The experimental finding is supported by a theoretical analysis, which was based on geometrical optics for a simple optical configuration that replicates the essential features of the optical system. The discrepancy in the location was measured using a monodisperse droplet generator, and this was subtracted from the droplet centres identified in the ILIDS images of a polydisperse spray without ‘seeding’ particles. This reduced the discrepancy between PIV and ILIDS droplet centres from about 1 mm to about 0.1 mm and hence increased the probability of finding the corresponding fringe patterns on the ILIDS image and glare points on the PIV image. In conclusion, it is shown that the proposed combined method can discriminate between droplets and ‘seeding’ particles and is capable of two-phase measurements in polydisperse sprays.     

Analysis of interpolation schemes for image deformation methods in PIV: effect of noise on the accuracy and spatial resolution

As testified by a previous article (Astarita and Cardone in Exp Fluids 38:233–243, 2005), a critical point that can influence significantly the accuracy of image deformation methods (IDM) for particle image velocimetry (PIV) is the interpolation scheme (IS) used in the reconstruction of deformed images. In the cited paper the effect of noise has been neglected and for this reason in this follow-up paper the influence of the IS, in the presence of noise, on both accuracy and spatial resolution is studied. Performance assessment is conducted using synthetic images with particles of Gaussian shape and with constant and sinusoidal displacement fields. Both the local and the top hat moving average approaches are investigated and the modulation transfer function, the total and bias errors have been used to evaluate the performances of IDMs for PIV applications. The results show that, when a high noise level is present in the images, the influence of the IS is less relevant than what was shown by Astarita and Cardone (Exp Fluids 38:233–243, 2005).     

Limits on the resolution of correlation PIV iterative methods. Fundamentals

The spatial resolution of correlation particle image velocimetry (PIV) is a frequently addressed issue that still raises scientific interest. In conventional non-iterative PIV, the spatial resolution limits are of common knowledge (Willert and Gharib (1991) Exp Fluids 10:181–193; Raffel et al. (1998) ISBN 3-540-63683-8, Springer, Berlin Heidelberg New York, among others). On the contrary, those advanced iterative multipass methods that use image distortion techniques or multigrid techniques present a more complex scenario. One of the concepts that raises more debate is the limiting effect of the interrogation window size. This paper focuses on the subject, trying to clarify key points. The results indicate that iterative algorithms using an appropriate weighting function eliminate the window size from the ensemble of spatial resolution limits.     

Dynamic masking of PIV images using the Radon transform in free surface flows

Particle image velocimetry (PIV) processing of free surface flow images often requires the use of digital masks to overcome the problems caused by the interface. In cases where a large number of particle images are collected it is essential that the time-varying boundary between the two phases can be tracked automatically to produce the binary masks. The Radon transform-based technique presented in this paper allows the automatic detection of the air–water interface in a stream of particle images acquired from a single camera. It is applied to time-resolved PIV measurements in the liquid phase of a stratified multiphase flow in a circular pipe. Accuracy estimations are provided using synthetic and real wave profiles. An extension to the more complex case of an overturning wave is also discussed.     

A vision-based hybrid particle tracking velocimetry (PTV) technique using a modified cascade correlation peak-finding method

A novel technique for particle tracking velocimetry is presented in this paper to overcome the issue of overlapping particle images encountered in the flows with high particle density or under volumetric illumination conditions. To achieve this goal, algorithms for particle identification and tracking are developed based on current methods and validated with both synthetic and experimental image sets. The results from synthetic image tests show that the particle identification algorithm is able to resolve overlapped particle images up to 50?% under noisy conditions, while keeping the root mean square peak location error under 0.07?pixels. The algorithm is also robust to the size changes up to a size ratio of 5. The tracking method developed from a classic computer vision matching algorithm is capable of capturing a velocity gradient up to 0.3 while maintaining the error under 0.2?pixels. Sensitivity tests were performed to describe the optimum conditions for the technique in terms of particle image density, particle image sizes and velocity gradients, also its sensitivity to errors of the PIV results that guide the tracking process. The comparison with other existing tracking techniques demonstrates that this technique is able to resolve more vectors out of a dense particle image field.     

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.     

A kilohertz frame rate cinemagraphic PIV system for laboratory-scale turbulent and unsteady flows

A kilohertz frame rate cinemagraphic particle image velocimetry (PIV) system has been developed for acquiring time-resolved image sequences of laboratory-scale gas and liquid-phase turbulent flows. Up to 8000 instantaneous PIV images per second are obtained, with sequence lengths exceeding 4000 images. The two-frame cross-correlation method employed precludes directional ambiguity and has a higher signal-to-noise ratio than single-frame autocorrelation or cross-correlation methods, facilitating acquisition of long uninterrupted sequences of valid PIV images. Low and high velocities can be measured simultaneously with similar accuracy by adaptively cross-correlating images with the appropriate time delay. Seed particle illumination is provided by two frequency-doubled Nd:YAG lasers producing Q-switched pulses at the camera frame rate. PIV images are acquired using a 16 mm high-speed rotating prism camera. Frame-to-frame registration is accomplished by imaging two pairs of crossed lines onto each frame and aligning the digitized image sequence to these markers using image processing algorithms. No flow disturbance is created by the markers because only their image is projected to the PIV imaging plane, with the physical projection device residing outside the flow field. The frame-to-frame alignment uncertainty contributes 2% to the overall velocity measurement uncertainty, which is otherwise comparable to similar film-based PIV methods. Received: 11 July 2000 / Accepted: 21 June 2001 Published online: 29 November 2001     

A novel PIV technique for measurements in multiphase flows and its application to two-phase bubbly flows

A new experimental procedure for performing simultaneous, phase-separated velocity measurements in two-phase flows is introduced. Basically, the novel particle image velocimetry (PIV) technique is a combination of the three most often used PIV techniques in multiphase flows: PIV with fluorescent tracer particles, shadowgraphy, and the digital phase separation with a masking technique. The combination of these three independent measurement techniques is achieved by shifting the background intensity of a PIV recording to a higher, but uniform gray value level. In order to combine the advantages of these multiphase-PIV methods, a new PIV set-up was developed. With this set-up the velocity distributions of the two phases are measured simultaneously with only one b/w camera. This experimental set-up is aimed at providing a means for characterizing the modification of turbulence in the liquid phase by bubbles. This phenomenon is often called "pseudo-turbulence".     

PIV measurement of flow around an arbitrarily moving body

This paper presents a PIV (particle image velocimetry) image processing method for measuring flow velocities around an arbitrarily moving body. This image processing technique uses a contour-texture analysis based on user-defined textons to determine the arbitrarily moving interface in the particle images. After the interface tracking procedure is performed, the particle images near the interface are transformed into Cartesian coordinates that are related to the distance from the interface. This transformed image always has a straight interface, so the interrogation windows can easily be arranged at certain distances from the interface. Accurate measurements near the interface can then be achieved by applying the window deformation algorithm in concert with PIV/IG (interface gradiometry). The displacement of each window is evaluated by using the window deformation algorithm and was found to result in acceptable errors except for the border windows. Quantitative evaluations of this method were performed by applying it to computer-generated images and actual PIV measurements.     

In-line imaging measurements of particle size,velocity and concentration in a particulate two-phase flow

A novel method is developed for in-line measurements of particle size, velocity and concentration in a dilute, particulate two-phase flow based on trajectory image processing. The measurement system consists of a common industrial CCD camera, an inexpensive LED light and a telecentric lens. In this work, the image pre-processing steps include stitching, illumination correction, binarization, denoising, and the elimination of unreal and defocused particles. A top-hat transformation is found to be very effective for the binarization of images with non-uniform background illumination. Particle trajectories measured within a certain exposure time are used to directly obtain particle size and velocity. The particle concentration is calculated by using the statistics of recognized particles within the field of view. We validate our method by analyzing experiments in a gas-droplet cyclone separator. This in-line image processing method can significantly reduce the measurement cost and avoid the data inversion process involved in the light scattering method.     

In-line imaging measurements of particle size,velocity and concentration in a particulate two-phase flow

A novel method is developed for in-line measurements of particle size, velocity and concentration in a dilute, particulate two-phase flow based on trajectory image processing. The measurement system consists of a common industrial CCD camera, an inexpensive LED light and a telecentric lens. In this work, the image pre-processing steps include stitching, illumination correction, binarization, denoising, and the elimination of unreal and defocused particles. A top-hat transformation is found to be very effective for the binarization of images with non-uniform background illumination. Particle trajectories measured within a certain exposure time are used to directly obtain particle size and velocity. The particle concentration is calculated by using the statistics of recognized particles within the field of view. We validate our method by analyzing experiments in a gas-droplet cyclone separator. This in-line image processing method can significantly reduce the measurement cost and avoid the data inversion process involved in the light scattering method.     

Limits and accuracy of the Stereo-LFC PIV technique and its application to flows of industrial interest

Particle image velocimetry with local field correction (LFC PIV) has been tested in the past to obtain two components of velocity in a two dimensional domain (2D2C). When compared to conventional correlation based algorithms, this advanced technique has shown improvements in three important aspects: robustness, resolution and ability to cope with large displacements gradients. A further step in the development of PIV algorithms consists in the combination of LFC with the stereo technique, which is able to obtain three components of velocity in a plane (2D3C PIV). In this work this combination is implemented and its performance is evaluated carrying out the following two different tasks:

On image pre-processing for PIV of single- and two-phase flows over reflecting objects

A novel image pre-processing scheme for PIV of single- and two-phase flows over reflecting objects which does not require the use of additional hardware is discussed. The approach for single-phase flow consists of image normalization and intensity stretching followed by background subtraction. For two-phase flow, an additional masking step is added after the background subtraction. The effectiveness of the pre-processing scheme is shown for two examples: PIV of single-phase flow in spacer-filled channels and two-phase flow in these channels. The pre-processing scheme increased the displacement peak detectability significantly and produced high quality vector fields, without the use of additional hardware.     

Digital particle image velocimetry

Digital particle image velocimetry (DPIV) is the digital counterpart of conventional laser speckle velocitmetry (LSV) and particle image velocimetry (PIV) techniques. In this novel, two-dimensional technique, digitally recorded video images are analyzed computationally, removing both the photographic and opto-mechanical processing steps inherent to PIV and LSV. The directional ambiguity generally associated with PIV and LSV is resolved by implementing local spatial cross-correlations between two sequential single-exposed particle images. The images are recorded at video rate (30 Hz or slower) which currently limits the application of the technique to low speed flows until digital, high resolution video systems with higher framing rates become more economically feasible. Sequential imaging makes it possible to study unsteady phenomena like the temporal evolution of a vortex ring described in this paper. The spatial velocity measurements are compared with data obtained by direct measurement of the separation of individual particle pairs. Recovered velocity data are used to compute the spatial and temporal vorticity distribution and the circulation of the vortex ring.