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Invited Paper

An automatic digital image processing

system for whole field flow measurement

T. Kobayashi, T. Saga

Institute of Industrial Science, The University of

Tokyo, 7-22-1, Roppongi, Minato-ku, Tokyo 106,

Japan

ABSTRACT

An automatic image processing system for measuringinstantaneous, whoie field of velocity vectors wasdeveloped. This system is connected with the classical flowvisualization technique (tracer injection method) andsophisticated image processing technique. The measurementsystem consists of a laser light source, a TV camera, alaser optical disk recorder and an image processorinterfaced with a 16 bit micro-computer. The tracerparticles injected into the liquid flow are illuminatedusing the pulsed laser light sheet and are tracked by the TVcamera. The images recorded on the laser disk are laterreplayed and sent to the image processor, and instantaneousvelocity vectors of whole flow field is automaticallycalculated. To explore the ability and usefulness of thissystem the complex flow fields have been investigated.

INTRODUCTION

An important subject of modern experimental fluidmechanics is the development of techniques for themeasurement of whole, instantaneous velocity. Conventionalpoint measurement techniques such as Hot-Wire Anemometry(HWA) and Laser Doppier Veiocimetry (LDV) have been widelyused for various flow measurements with sufficient accuracy.However, the difficulties of the calibration of multisensorhot-wire probe and the optical arrangement of laser dopplervelocimeter become to decline the practicability of theirtechniques. It is expected to develop a new technique which

Transactions on Information and Communications Technologies vol 5, © 1993 WIT Press, www.witpress.com, ISSN 1743-3517

348 Visualization and Intelligent Design

overcomes this basic problem.

Particle-Imaging Velocimetry (PIV) enables the dynamicmeasurement of flow velocity, by the tracking in the realtime the movements of fine particles injected into a flow[1],[2],[3]. Several outstanding characteristics havegenerated the great advantage in PIV : © two-dimensionaland three-dimensional information can be logged in real-timefor multi-points over a whole field of the flow, (2) fromthis information the flow structure can be interpreted, (3)the need of the velocity calibration is eliminated, (D themethod is applicable to complex flows, (5) measurement is nocontact, (6) data can be automatically processed with ease.

With these advancements of PIV, we have been developedan automatic image processing system for the flowmeasurement. The utility of this system for detecting theflow structures is demonstrated.

MEASUREMENT TECHNIQUE AND INPUT IMAGE

The flow velocity is calculated by tracking theparticles injected into the flow field. Motions of particlesare observed simultaneously by TV camera. By processing theconsecutive TV frames, instantaneous particle positions arereconstructed, and then the path of each particle over theseveral time steps is identified. The flow velocity vectoris calculated from the displacement of each particle duringa short time interval.

MEASUREMENT SYSTEMShown in Fig.l is the measurement system designed

specifically for PIV, consisting of a illumination source(SPECTRA PHYSICS 2016 ; 4W Argon laser), a charge-coupleddevise camera (SONY XC 007 ; NTSC video format), a laseroptical video recorder system (SONY LVR,LVS-5000 ; 48000frames capacity), an image processor with 16 MB externalimage memory (NEXUS 6400) and a 16 bit micro-computer (NECPC9801 VX) . The image processor and the video recorder areinterfaced with the host computer which controls wholeoperations in this system. Image data from the flow fieldare logged directly by the TV camera and analyzedautomatically. For an automatic image processing,consecutive images from the TV camera are recorded on theoptical video disk. By the command from the host computer to


Visualization and Intelligent Design 349

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L.

sor

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CPI B

t Coniput

<ft

:er-

Pr inter

T

C3c 1RS232C

Color Hard Copy

Fig. 1 Measurement system

the video recorder, the images of the disk are selected andare sent to image processor. The monochrome analog videosignal of NTSC video format are digitized into 256 graylevels over 512 X 480 pixels by the image processor. Thedigitized images are then thresholded by an adequate graylevel to extract the images of particles from those of thebackground. Finally, the gravitational center of eachparticle image is calculated by the image processor andtransferred to the microcomputer. Both image acquisition anddata reduction are executed automatically by the originalcomputer programs.

CODED ILLUMINATIONFor covering wide range of flow speed measurements, a

suitable coded pulsing illumination is introduced into themeasurement system. The illumination system, shown in Fig.1, consists of an Argon laser source, an acousto-opticmodulator (AOM) which connected with the TV camera through apulse controller, an optical fiber and a lens system. Thelaser beam passes through a series of optical components to



produce a modulated sheet of laser light. The temporal lightillumination is obtained by using the scattered light of thefirst order which is produced by the AOM. The illuminationis synchronized with the vertical and horizontal blankingsignals of the TV camera. Figure 2 shows the two typicalillumination codes for the lov and high flow speedmeasurements, and the input images obtained by using those

Frame(l/30sec)

Odd Field Even Field

1,'dt,

n^T,

4-

T

dtt-

i

[Field Integration]

(a) Illumination code for low-speed flow

dtz

II

dt.

To

[Frame Integration]

(b) Illumination code for high-speed flow

Fig. 2 Illumination code



codes are shown in Fig.3. In order to adapt to various flowconditions, the timing of illumination Ti at the video frameand the pulsing time dti can be adjusted respectively byusing unit time period (1H = 63.56 us) in this system. Theillumination times of the laser light also can be changed.At the low speed illumination code, the flow field isilluminated once at each field (Fig. 2(a)). In the case of

frame

.CDJ,


(a) Input images by low-Speed illumination code

Frame

• 1 1

(4) ®®.®®


(b) Input images by high-Speed illumination code

Fig. 3 Frame image and its' divided field images



the high speed flow measurements, the i 1 luminatio.n code issettled as shown in Fig.2 (b). In this mode, the flow fieldis illuminated one time at the odd field and three times atthe even field. Furthermore, the electric charge mode of theTV camera is changed between two illumination codes. Thefield integration mode is used for the low speed code andthe frame integration mode is used for the high speed one.By selection of the illumination code and the electriccharge mode, the particle images during several time stepsare photographed on a frame image, as shown in Figs.3 (a)and (b).

INPUT IMAGESince the information at each field image is required

for the present particle tracking, the frame image isdivided into the odd field and the even field before theparticle tracking. The input image of NTSC video format,consisting of 525 horizontal scan lines, is dissected intotwo fields, the odd field and the even field. Each field has262.5 scan lines, which are combined and interlaced toproduce a complete frame. At first, the frame is dividedinto two field images by using a image dividing mask. Next,to fill up the left pixel densities of both field images bythis frame divide, the pixel densities are interpolated byusing the surrounding pixel densities. Thus two new fieldimages are produced from a frame image. Figure 4 shows atypical field image produced by using the low speedillumination code. This process is continuously performed onconsecutive frame images before the particle tracking.

Fig.4 Instantaneous tracer particles of the produced fieldimage by using a low-speed illumination code



IMAGE ANALYSIS

Calculation procedure of velocity - vectors from theproduced field images consists mainly of three steps, theextraction of particle position, tracking of particle anddetermination of particle path. There are several proposalsof tracking motions of tracer particles in video image, butchose have the same fundamental principle : a series ofimages of particles during four time steps are superimposedto determine the distance which the particle has travelledand thence the velocity vector. The most crucial taskperformed by the system software is to identify the sameparticle over series of images. The details of tracking andidentification algorithm is discussed in [4], [5], [6],

At the low speed illumination code, instantaneousparticle positions at each illumination time Ti are obtainedon the consecutive each field image, independently (Fig3(a)). In this case, a set of four consecutive field imagesare used for the particle tracking and the determination ofthe particle path.

In the case of the high-speed flow measurements,particle positions of same particle during the time TI to Tgwere superimposed on a frame image by selection of the high-speed illumination code and the frame integration chargemode as shown in Fig. 3(b). However, these particles have noinformation concerning the time history, it is needed to getsome information of the time from the input image. Here, toextract the initial position of particles, the images of theodd and the even fields are subtracted from each other. Bythis operation, all of the initial particles with positivevalues of image density and the terminal positions withnegative values are identified in the frame image. Once theinitial position is determined, the particle tracking isaccomplished by the prediction of displacement and thedirection of the particle during four time steps.

EXPERIMENTAL FACILITY AND PROCEDURE

To explore the ability and the usefulness of thepresent technique, the system is applied to two kinds ofcomplex flow fields. The flow measurement in a rectangularchannel with a backward-facing step was focused on theevaluation of the measurement accuracy of present technique.



In the measurement of a casting model which is scaled downby 1/7 casting in metallurgical process, we emphasis on theview to confirm the applicability of the system for thecomplex flow measurement.

The working fluid is water, and the fluid motion isvisualized by fine particles injected into the fluid. Theparticles are made of Nylon 12, specific density of which is1.02 and is closely equal to that of water. The meandiameter of particles is about 100 urn.

BACKWARD FACING-STEPThe experiment is carried out for the two water models

as shown in Figs. 5 (a) and (b). The transparent rectangularchannel has a 50 mm height of backward-facing step. Theexpansion ratio is 1.5, and the channel width is 2h. Thefree stream velocity UQ at the 5h upstream of step is 0.8m/s, and the Reynolds number based on UQ and h is 4 X 10*.The 2 mm thick of coded illumination is provided into themid-span plane of the channel, and the particle motions inthe plane are observed by the TV camera. Measuring region istaken over 3h upstream of the step and 12h downstream. It isdetermined that the measuring domain of each experiment is3h X 3h X 0.04h to consider the measurement uncertainty. Inthis case, the image resolution is 0.31 mm / pixel.

CASTING MODELThe main components of the casting model are a curved

and transparent rectangular parallel channel and atransparent injection pipe (Fig. 5(b)). The channel hasdimensions of 214 mm width, 34 mm depth, 3000 mm length, andthe pipe with two injection nozzles is placed at the channelcenter (; the inner diameter of the pipe is 10 mm and thenozzle diameter is 10 mm). Tracer particles arecontinuously introduced at the pipe inlet. Water flowpassed through the pipe is injected into the channel throughthe two nozzle's, and the jets are induced with twosymmetrical cavity flows in the channel. Reynolds numberbased on the pipe inner diameter d and the average velocityin pipe UQ ( = 1.0 m / s) is 1 X 1 0\ Measurements are made ina central vertical cross section (100 mm X 100 mm) of thechannel illuminating by the 1 mm thick of the codedi1luminat ion.


Visualization and Intelligent Design

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2hXX

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x/h

(a) Rectangular channel with a backward facing-step

Flow

t

Coded Illuminationof LLS

Injection Pipe

Nozzle

Measuring Region(lOOmmx 100mm)

(b) Casting model

Fig. 5 Experimental apparatus

ZCD Camera



Table 1 Illumination Code

Cc

1

2

3

1

2

3

Bac

)de

(1)

(h)

(h)

Ti

356H

50H

100H

(1)

(h)

(h)

100H

100H

220H

:kward

T2

890H

260H

260H

Cast in

356H

200H

270H

Facing

T3

1406H

280H

280H

g Model

625H

400H

300H

Step

Ti

1931H

360H

360H

dt

2H

2H

2H

88IH

510H

330H

10H

10H

IOH

1H = 63.56 us

1 : Low Speed Illumination Code

h : High Speed Illumination Code

The illumination codes used in this experiments are

shown in Table 1.In order to check the measurement accuracy of present

technique, the velocity measured by PIV was compared withLDV data. The measurement volume of LDV has an ellipticalshape, in which the diameter is 49 urn and the length of beamdirection is 189 urn. Scattered light from the measuringpoint is collected by photomultiplier and the signal isprocessed by an universal wave analyzer. The sampling ofbursting signal at each measuring point is performed during1 minute.

RESULTS AND DISCUSSIONS

Measured velocity vectors are scattered at random inthe flow field, and are rearranged by the interpolationmethod. The flow field around the backward facing-step isdivided into 46 X 25 non-uniform grid points, and velocityvector on the grid point is interpolated from severalneighboring local velocity vectors. There are the number nof velocity vectors near a grid point. The interpolationarea is defined at the vicinity of grid point as shown inFig 6. From velocity vectors of nCg combinations in the



K L

m

Node

InterpolationArea

Fig. 6 Interpolation of mean velocity on the grid point fromthe measured velocity vectors

interpolation area, the grid point each velocity value canbe calculated by the following equation.

1 dxK dy»T

1 dXL dyu

1 dxm dym

•

' U '

dudx

du

=

U/

UL

.Urn.

The mean velocity value of grid point can be obtained byaveraging all of the interpolated values.

In this experiment, 300 frames of images were processedat each 3h X 3h measuring domain, and 8,877 instantaneousvelocity vectors were obtained. About seven to teninstantaneous velocity vectors existed in everyinterpolation area. The mean velocity vectors on the gridpoints are interpolated by these neighboring velocityvectors, and the resultant by PIV is shown in Fig. 7. Toevaluate the present technique, the mean velocity profilesat the positions of x/h = 2.67 and 6.22 are compared withthe LDV results. As shown in Fig.8, the present resultsagree well with the LDV results. It is suggested that thepresent technique has high accuracy and reliability.



• • • • r " * " " " ; ~:::::: I: : :: : : :::::: :

(a) 5 (b) X/h 10

Fig.7 Flow over a backward facing-step

— LDV-*-PIV

1 2y/h

(a) x/h = 2.67

.... LDV— PIV

1 2y/h

(b) x/h = 6.22

Fig.8 Comparison PIV and LDV results



Because of the applicability of the system is one ofthe important factor of the velocity measurement, weconformed the system function by the measurement of thecomplex flow field in casting model from this view point. Atypical results of velocity distributions by using the threeillumination codes are shown in F.igs.9 (a), (b) and (c) . Inthese figures, consecutive 30 frames (during 1 second) datawere summed up, and the number of velocity vectors of eachfigure are 34, 526 and 45, respectively. From these figures,we can easily understand that this flow field consistsmainly of the jet flow and the cavity flow induced by thejet. Final data are overlapped summation with a unifiedtime base as shown in Fig.9(d). Figure 10(a) shows t he-interpolated velocity vectors from the Fig.9(d), and is alsocompared with the LDV result (Fig 10(b)). As shown in thefigures, the profiles of averaged velocity distributions byPIV agree well with LDV results. At the velocity measurementand data reduction, it takes almost two days to obtain theaveraging velocity on 1 1 X 1 1 grid points by using LDV, andin the case of the PIV measurement on 3 1 X 3 1 grid points weneed only five minutes. It is clearly shown that the PIV hasexcellent performance for the full field velocitymeasurements.

In the present technique, the illumination code shouldbe determined carefully according to the flow condition, andit is clear that a large number of the measured velocityvectors is required for an accurate prediction of the gridpoint velocity.

CONCLUSIONS

In conclusion, we have been presented an automatic imageprocessing system for whole field flow measurement whichconsists of a coded illumination source, a high-speed imageprocessing algorithm, and an image processing system.(l)The ability and utility of this system is validated to

the complex flow measurement over a backward facing-stepin water channel. The mean velocity profiles measured bythe present technique is in close agreement with LDV data.

(2) With good accuracy, the system performs a full flowfield velocity mapping, rapidly and automatically.It has been demonstrated that the technique is an

important element in experimental research .of complexturbulent flow fields.



1

_\ V

(a) Code (b) Code 2

i

(c) Code 3 (d) Summed up velocityvectors

Fig. 9 Velocity Measurements in the casting model

(a) Velocity Vectors on33X 33 Grid Points (PIV)

(b) Velocity vectors on1 1 X 1 1 Grid Points (LDV)

Fig. 10 Comparison PIV and LDV results



REFERENCES

1 .Kobayashi,T., Advances in computer-aided flowvisualization, Flow visualization VI, Springer-Verlag, 25-37, 1992.

2.Hesselink,L, Digital imageprocessing in flowvisualization, Annu. Rev. Fluid Mech., 20, 421-485, 1988.

3.Adrian,R.J., Particle-imaging technique for experimentalfluid mechanics, Annu. Rev. Fluid Mech. 23, 261-304,1 991 .

4.Kobayashi,T., Saga,T. and Segawa,S., Multi-point velocitymeasurement for unsteady flow field by digital imageprocessing, Flow Visualization V, Hemisphere, 197-202,1990.

5.Kobayashi ,T., Saga,T. and Sekimoto,K. , Velocity measurementof three-dimensional flow around rotating parallel disksby digital image processing, ASME FED Vol.85, 29-36,1989.

6.Kobayashi ,T., Saga,T., Haeno,T. and Tsuda,N^ Development ofa real time velocity measurement system for high Reynoldsfluid flow using a digital image processing design, ASMEFED Vol.128, 9-14, 1991.


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