High-Speed Photography applied to Laser Cladding Process

Fabrice Mériaudeau, Frederic Truchetet, Christophe Dumont

Laboratoire LE2I12 rue de la Fonderie, 71200 Le Creusot, France.

Tel (33) 85-80-30-30, Fax (33) 85-80-36-15Email: F.Meriaudeaugere.u-bourgogne.fr

ABSTRACT

The laser cladding process consists in adding melting powder to a metallic substrat. The process usually involves thedelivery offine grained alloy powder blown into the melt pool during the laser irradiation. The temperature ofthe grains whenthey reach the surface and their speed within the laser beam are extremely correlated and influe on the quality of the coating.We present three methods which can be used to measure the speed of the particles in the powder stream; they all make use ofdigital images obtained with a standard matrix CCD camera and a strobed lighting. The first method, which we call the basicone, allows speed measurements in a slim cross section of the powder stream. Thanks to its low requirement in calculationamount we were able to implement it in a stricly software design for real time application (1 image/2Oms). In the secondmethod we work on the Fourier Transform plan of a strobed image, between two flashes the particles have moved from thesame distance this periodic distance represents a specific frequency which is estimated in the Fourier space. In the thirdmethod, we strobe the image using three color filters and obtain a RGB image. The autocorrelation function of the imageprovides us with information related to the speed of the particle. The particularity of the two last methods is theircomplementarity. Indeed, the FFT gives good and averaged results for wide area, it is a large scale method. At the opposite,the three colors imaging method is powerful for small scale study.

KEYWORD LIST

Particle speed measurement, CCD camera, strobed lighting, image processing, laser cladding.

1 . INTRODUCTION

In many industrial applications, the material surface is, most of the time, the preponderant factor in the life time of thepiece. In such cases, it is important to be able to improve the superficial properties ofthe material"2'3'4. One ofthe numerousknown solutions 5,6,7,8 is to depose, where the constraints are supposed to occur, a hardfacing alloy which have the desiredwear resistance properties: one calls that the cladding process.

Thus, the goal of the laser cladding process consists in obtaining an homogeneous surface layer with a strongmetallurgical bond to the substrate and only a low degree of dilution. The process usually involves the delivery of fme grainedalloy powder blown into the melt pool during the laser irradiation.9"°"12.

The speed of the particles is one of the most important process parameter. Indeed, this one defmes the irradiationtime of the particles before reaching the surface, thus leading to different states of the powder such as liquid or solid. If theparticles are still in a solid form, the irradiation time will define whether or not the particles have an homogeneoustemperature while reaching the surface.

This paper is dedicated to a special emphasis on powder speed measurement. After presenting in the first part thelaser cladding process, we propose a brief study of the influence of the speed of the particles on the process. In the third andmain part of the paper we present three different methods involving CCD cameras and strobed shootings enabling us to obtainmeasurement of the speed of the particles. In the first method, which is very basic from image processing point of view, wepropose an algorithm allowing the reconstruction of the trajectories of some isolated particles. The second method, using aFourier transform approach, leads to an evaluation of the mean speed of the particles. The third way explored here makes useof superimposed color images and it permits to measure the speed of some particles anywhere in the observation field. Wewill discute about the accuracy of the different methods and the computation time required by those methods. The last partwill be dedicated to a summary of our work and what we expect for the future.

2. LASER CLADDING PROCESS

As written in the introduction the laser cladding process (see figure 1 below) involves fme delivered grain powderswhich are (in our case) coaxially injected in the laser beam. According to both the laser beam power and the speed of the

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particles, the powder will reach the surface (in the melted pool) either in a liquid form or still in a solid aspect. In order toassure a good metallurgical bond the substrate has to be slightly melted (not to much in order to avoid the creation of alloy).

Figure 1. Principle ofthe laser cladding process

The quality ofthe laser clad tracks is strongly dependent upon the processing parameters and the powder feed rate.A lot of works have been carried out in order to find the parameters which needed to be controlled and carefully

checked during the process in order to imirove the quality ofthe track.We only quote here few articles 17 1 that one can fmd in the exhaustive literature. One can say that the main parameters

are the processing speed, the mass feed rate , the laser power, the beam diameter and the powder speed. According towhatever configuration one adopts: predeposed powder, coaxially blown powder, laterally blown powder, the parameters donot have the same consequential effects, moreover ifyou used for example a coaxially blown powder system, you also have tocope with the carriage gaz flux and the protection gaz flux.

3. INFLUENCE OF PARTICLE SPEED

The speed of the particles is a very important parameter involved in the process. It defines the interaction time of theparticles with the laser beam before reaching the substrate surface.

If one looks at the heat equation which can be applied herein to an homogeneous, isotropic and limited medium;assuming that no heat sources and no well of heat within the particle exist, one can write the equation as follow:

1T ldki_____>1=0 (1)aat kdT\ grau /

where:AT is the temperature Laplaciana is the thermal diffusivity (m2.s')k is the thermal conductivity (W.m1.K1)

Assuming that the thermal conductivity does not vary with temperature, Huetz35 has solved the heat equation for asphere and has given the solution for a fast increase of the temperature at a point M' situated at a distance r from the pointsource M (r diameter of the particle). The temperature can be written:

T(r,t) =k

e (2)

(at)2

After differenciation, the time when the temperature is maximal at the point M' will be:

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Powder andlaser beam

Melted pool

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r2tM (3)6.a

Thus, knowing the speed of the particle we are able to know if the particles have an homogeneous temperature whenthey reach the surface. This parameter is important in order to prevent the apparition of cracks due to the non-melted particles.

As one can see on the table I, the required time for the particles to reach an homogeneous temperature while reachingthe surface is around the tenth of the milliseconde. As we shall see above, the irradiation time in our experimental set-up isgreater than this value, leading to a good quality track.

Stellite 6 I

I r6Om l.58.104s

Ii r8Om 2.8l.1Os

Table 1 : Required time in order to get an homogeneoustemperature within the particle

Sometimes with an output laser power important enough, the particles can reach the fusion temperature before reachingthe surface. The fact is very important, indeed in the paper 36 we can note that when the powder has reached the fusiontemperature, the relative required energy in order to assure a good quality coating (strong metallurgical bond) is weaker thanfor non melted particles during the flight.

Thus if one looks at the energy transfer, the internal energy variation within a powder grain can be written as:

L\Q = m(C . AT + & AH ) (4)with:

m: mass ofthe particle (kg)C: Specific heat (kg.m-3)AH : Fusion enthalpy (J.kg-l)

: step function 1 if T>Tf= 0 if T<Tf

According to our assumption, we can write that the internal energy variation is equal to the absorbed energy. As amatter of fact, it can be written as a fonction ofthe incident energy:

dQabs I0ASdt (5)where:

l the irradiance (W.cm2)A absorption coefficientSp = itd2/4 , d diameter ofthe particledt: interaction time (s)

Ap is a very complex coefficient changing both with the temperature and the wavelength as well as with the surfacestate of the target. We assume a value of 0.47 for Ap from previous experiment8.

We would like to say here that we assume that the system is adiabatic and we do not take into account the energy lossesdue to heat transmission (Boltzman) and heat convection (Newton).

On the graph displayed below (fig 2), we plotted the particle temperature versus the irradiance for different irradiationtime. As one can see, the speed of the particles which is directly linked to the irradiation time is a very important parameter,especially for particles with a high absorption coefficient.

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Figure 2: Evolution ofthe powder temperatureversus the laser power irradiance for various interaction time

4. SPEED MEASUREMENTS

In order to investigate the speed of the particles we just used one CCD camera, which is cheaper than a set upinvolving a Doppler anemometer. We would like to say here, that some work have used this kind of system9' but all of themhave worked in a very low mass feed rate range in order to detect speed or! and trajectory at the center of the powder spray.Using these feed rates they were not able to obtain realistic tracks.

4.1. Basic method:As the previous quoted authors we have tried, using a strobe and an algorithm which was able to detect trajectories, to

get information related to the speed ofthe particles. As one can see on the figure 3, it is easy to determine trajectory and speedof excentric particles which do not participate in the cladding process, but it is impossible to investigate the center of thepowder spray which is the really of ti

In order to investigate the speed of the particles both within the core of the powder distribution and with a reasonablemass feed rate, the authors used a CCD camera with a variable integration time (electronic shutter) and a laser light-sheet inorder to inspect the powder distribution (Schlieren method)37. After having calibrated the camera, it is very easy for theoperator to find the speed of the particle knowing the selected integration time. Indeed the measure consits in thedetermination of the trace length in a given direction. Knowing the lenght, the operator finds thanks to the calibration the reallength, and he can determine the speed because in knows the integration time. The results are displayed below (figure 4).Comparison with the results found using a doppler anenometer shows a great accuracy of the system.

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FlightTime 7,2 10-3 secondesv=2,5 rn/s

2500

2000

1500--

I— 1000

500

0 1000 2000 3000 4000 5000 6000 7000 8000 9000 10000

Irradiance(W!cm2)

FIightTime 6,5 10-3 secondesv2,76 rn/s

figure 3: trajectory and particle speed

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Figure 4. Variation ofthe particle speed versus the distance nozzle/sensorand comparison with the results provided by a Doppler Anemometer

The main problem of this method is the fact that the operator is required to achieve a cross section (as displayed on theabove graphic). In view to avoid this disadvantage, we developed an automatic extraction procedure. This method is similar tothe one employed by Galloway38 for texture analysis. After having proceeded to a binarisation of the image we count thenumber of traces, their lengths and their starting point. This is done using a block color (8 neighboors) algorithm39. As aresult, we obtain a matrix which contains for each starting point and each length, the number ofpixels. Those data enables usto withdraw nonprobable data (particles crossing the lighting plane).

4.2. Fourier transform method:In order to alleviate the experimental set-up we have tried another method: calculate the Discrete Fourier Transform

of an image strobed with two flashes. Indeed, if one assumes the following theoretical model for the powder modelization, onefinds that it is possible to have access to the speed ofthe particles while knowing the monodimensionnal DFT.Indeed if one assumes that a particle can be represented by a known luminance profile, gaussian for instance (6), and that theirrepartition along a line follows a Poisson's distribution (x) which probabilty follows the expression (7).

f(x) =e (6)

P(N,t) = ()N et (7)

where X is the average evenement number by space unity and P(N, t) represents the probabilty of finding N particles in the

space T.One line of the image can be represented by the expression:

11(x) =f(x)*6(x) (8)where * is the convolution product symbol.The signal due to the particles which have moved (strobed) ('2(x)) can be written:

12(x) =d (x) * 6 (x) (9)where d means the translation done by the particles.Thus the signal captured after the second strobe flash can be expressed by:

I(x)=11(x)-i-12(x) (10)If one expresses the previous equation in the Fourier space, this would lead to

(u) ='()'2() (11)

where 1(u) is the Fourier transform of 1(x)Expression (11) can also be written as follow:

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E

0Va0.

0 2 4 6 8 10 12 14 16 18 20

distance nozzle/sensor (mm)

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I(u)= f(O).ai(U)(1+ e20d) (12)Leading to:

2 2 2

Or: I( 2A6ai(0) e2j02 (13)

I(u) = 2f(u) ai( .(1+cos(-2ud) (14)

If one investigates, the special frequencies for which the expression (14) is equal to zero, one has to solve:2 2

f(o) ai(°) 11 + e22 = 0 (15)

The three terms of the expression (1 8) can be studied separately. On the 41, 42 one can find that:2

f(u) = e°2 (16)

andA 2

öai(0) X26(o)+ (17)

Thus the resolution ofthe equation leads to:A 2

2

f(u) (X23(u) + 2).1 + e2j0 0 1 + cos(2cod) = 0 (18)

which gives:A2 2 1 k

f(u) .(22ö(u)+X).1+e20 =Od=—+-- kEZ (19)2u Uthus the monodimensional square modulus of the DFT enables to get information to the translated distance. Knowing the timebetween to flashes, we are able to find the average speed of the particles.The main problem linked to this method, is the fact that the translation has to be very small to prevent both the effect of theacceleration and to find a too small frequency which could be confounded with the noise of the image. The authors have beenable to simulate this (see figures 5 and 6), but were not experimentally able to strobe the signal fast enough in order to obtainexpected results. But,we think that this method could be very accurate and fast (using DSP circuits for FFT calculation) with amore convenient experimental set-up, and we are still wc

* *4

* 4 44d

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Figure 5: Strobed particles with a long translation d and the DFT result

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• • .S • a• •• • •• •Figure 6: Strobed particles with a short translation d and the DFT result,

showing that it is easy to determine the translation distance.

4.3. Three colors method:Another method that we have used, was what one can call a two or three colors imaging velocimetry. The principle is

very simple43. We use a color CCD camera and we strobe the image using a very high speed motor (can reach 36000tour/mm) on which we had previously put three colored filters (red, green and blue). The acquired image (see figure 7) is thensplitted in three images, corresponding toth' 8).

e corresponding to the Red color

Thus if one assumes that S1(x,y) is the signal provided by the red particles, S2 (x,y) the signal provided by the blue particles.Then we have the relation S2(x,y)S1(x-h,y-t), where h and t correspond to the translation effectuated by the particles. Afterhaving binarised our images, we soustracted each image to the other in order to remove both the blue and green componentsin the red image, as well as the noisy area. The fmal images are displayed below:

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Figure 9: Image correspondng to the red color and the blue colorThen, when we do the intercorrelation function between the two images, we have:

= S1(i,j).S2(i+'c,j+m) (20)

Where n is the number of particles of the signal S1(x). If one takes into account the previous relations between the two signals,then one can write:

n(21)

The function is now defined as an autocorrelation function, thus we know42, that an autocorrelation function is maximal for anargument equal to zero. Thus from equation (21), one finds that, as expected, the maximal is obtained when:

h=-rt=rn (22)

Therefore, knowing t and h we are able to define the translation distance, and with a good camera calibration we are able toobtain the following results: figure 10 and 11.

Figure 10: Correlation of the blue and red images, the white rectangle indicates the area on which the intercorrelation hasbeen achieved

h

t

Figure 11: Result of the correlation between the two imagesWhen one takes the maximun of the intercorrelation function, one finds: figure 12.

As shown, we performed this task only on a tiery small area because the processing time is very long due the high number ofoperations required. But as the previous method, tools like DSP could increase the processing speed and woud able toperform the treatment over the whole image.

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Figure 12: Extraction ofthe maximum ofthe intercorrelation function

5. CONCLUSION

As a mailer of fact, at this very point of view of our work we think that the best solution in order to extract theparticles speedusing the CCD technology would be to use the first displayed method (Shclieren method) if one is interested by fast results.The problem is that measurement is obtained only for particles contained in a slim longitudinal cross section during theirflight time. The DFT can be also accurate and fast and it provides an interesting integrated view of the speed of all theparticles but we only developed a monodimernsionnal model which will need to be extended to two dimensions under certainassumptions, moreover in order to be able to use the DFT, the operator needs a powerfull system in order to hastily sample theimage. The three colors method gives some interesting results for a detailed study of part of the viewed field, the price to bepaid is the use of color camera and an amount of calculation directly related to the area under study.

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