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Feasibility Study of Infrared Detection of Defects in Green-State and Sintered PM

Compacts

Report No. PR-05 - #2

OBJECTIVES The objective of this research is the development of a novel thermo-electric testing apparatus capable of detecting surface and sub-surface flaws in green-state compacts. After establishing viability of infrared testing, this research is to be applied to conduct on-line testing of moving parts following compaction. We expect to rely on natural cooling for simple surface defect detection for rapid inspection and on electromagnetic power deposition for complex subsurface defects for high resolution inspection. The active, electromagnetic power deposition is based on the principles of pulsed thermography whereby the PM specimen is subjected to a heat pulse (or step input) that can be synchronized with a detection system that includes an IR imager, a processing unit, and a computer with specialized software. The stated milestones identified by our focus group members for this fall meeting include:

A) to continue the theoretical investigation to incorporate the modeling of defects, power deposited and part interaction if the source relies on electromagnetic coupling,

B) to perform additional on-line testing at a different facility and test more

complex parts and parts manufactured at higher press speeds,

Research Team: Reinhold Ludwig (508) 831-5815 ludwig@wpi.edu Souheil Benzerrouk (508) 831-6797 souheil@wpi.edu

Focus Group Members:

Ian Donaldson GKN Sinter Metals Worcester, Chair Richard Scott Nichols Portland Michael Krehl Sinterstahl Hannes Traxler PLANSEE Aktiengesellschaft

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C) to investigate an alternative heat source to reduce/eliminate the effects due to electric contact resistance, and to reduce instrumentation complexity if the inspection systems is implemented on the factory floor, and

E) to continue the research of new data/image analysis techniques that ensure

reliable detection of surface and subsurface defects.

APPROACH The research approach identified four major tasks to be conducted during the spring-fall 2005 period. Specifically, they involve:

• Further investigation and refinement of the on-line IR testing and its requirements such as system calibration at Nichols Portland. In addition, tests with different part shapes, sizes and densities need to be conducted.

• Exploration of the possibility of relying on natural convection that can be

combined with on-line testing. This allows observing the differences in cooling rates between small parts and larger ones under production conditions.

• Proof-of-concept development of using a contact-less current injection

methodology by exploring various induction heating units and coils and possibly designing a custom coil system. In addition to testing commercial sources, a basic numerical model is to be built to ensure validity of the concept.

• Further investigation into adequate data analysis algorithms. This can be

performed through evaluating advanced image analysis procedures in isolation or in combination.

ACCOMPLISHMENTS The researchers can report the following accomplishments:

• A theoretical solution was devised that allows AC current excitation and that includes a defect approximation model based on an electric dipole representation.

• On-line testing and data collection was performed at Nichols Portland in Portland,

ME, where complex gears were successfully monitored “thermally” as the parts exit the compaction press. The results include different viewing angles.

• A test station was assembled for a contact-less eddy current injection scheme.

This includes an induction heating unit capable of delivering bursts of electromagnetic power, a camera system synchronized to the drive pulse of the

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induction heating unit, and a supervisory computer system to process and evaluate the thermal data.

• Extensive tests were conducted to investigate various parts with different sizes at

different test frequencies in an effort to study skin effects along with thermal time constants.

• A basic induction heating numerical model was constructed that enables the study

of all mechanisms associated with inductively coupling electric power into powder metallic parts.

FUTURE WORK For the next quarter we intend to continue the experimental and instrumentation work with particular emphasis on:

• Extending the theoretical studies to include pulsed thermography and defect depth and shape extraction,

• Completing the comprehensive FEM model to solve the forward electro-thermal

problem,

• Designing a data collection and analysis software that will enable us to make sample integrity decisions instantly,

• Integrating the option of extracting feature (defect) size, shape and depth from the

thermal signature into the analysis software

• Continuing the instrumentation effort to complete an apparatus capable of delivering electromagnetic heating while evaluating the part for defects

REPORT ORGANIZATION This report is organized in two appendices as follows: Appendix A – Contains the technical data from our testing at Nichols Portland. Specifically, an overview of the data collection is presented and a basic thermal analysis is shown that supports the versatility of the method. Appendix B – Contains our paper presented the 32nd Annual Review of Progress in Quantitative Nondestructive Evaluation, Brunswick, Maine, July 31-Aug 5, 2005. This paper summarizes the foundation of the electro-thermal defect detection scheme as applied to green state PM compacts. It summarizes the experimental results accomplished thus far.

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ACKNOWLEDGEMENT We would like to extend our gratitude and thanks to our focus group members for their guidance and their valuable inputs throughout this project. Especially, we would like to thank Richard Scott (Nichols Portland) and Ian Donaldson (GKN Sinter Metals, Worcester) for providing the facilities to complete our on-line testing, for the samples they supplied and their insightful inputs. We would also like to thank Hannes Traxler (PLANSEE Aktiengesellshaft) and Ulf Gummeson for their continued support and their encouraging remarks about this project.

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Report No. 05-#2 APPENDIX A

ON-LINE TESTING AT NICHOLS PORTLAND

Numerous tests have been conducted in an industrial setting without special requirements and without any change to the production line arrangement. The purpose of these product line investigations is to establish a realistic baseline for the background IR radiation. One key objective is to confirm the ability of the IR inspection system to capture thermal data from moving parts. This presents a unique challenge, as the camera system must be able to dynamically focus on a moving target as well as capture a significant number of images for reliable image processing purposes. The first set of tests presented in our last report (Report No. PR-05-#1) was performed at the Worcester facility of GKN Sinter-Metals. Figure 1 shows the green-state P/M sample. The compact is 55mm in height by 20mm in diameter and is typically manufactured at a rate of approximately 500 parts/hour.

Figure 1: Picture of the P/M part imaged in an industrial setting.

The most recent evaluations were conducted at the Portland facility of Nichols Portland. Here more complex parts (gears) shown in Figure 2 were observed at different production lines and from different viewing angles. The press rate of 900 parts/h resulted in an approximate speed of 0.2m/s over the attached conveyor belt.

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Figure 2: Picture of the P/M gear imaged at Nichols Portland.

The following IR images represent 2D surface and line profiles (recorded along the dotted line) recorded with an IR camera positioned 50cm away (viewed from the side) and operated at a frame rate of 30Hz. The field of view of the 240 by 320 pixels is 15cm by 15cm. The total line length of 10cm is subdivided into 180 points (i.e. with a point-to-point resolution of 0.5mm) whereas the thermal pixel intensity is displayed in discrete increments from a baseline of 0 (or 200K) to 260 (or 460K).

1 cm

0 20 40 60 80 10 0 1 20 14 00

5 0

10 0

15 0

20 0

25 0

D is ta nc e a lo ng p ro fi le

Pix

el In

tens

ity

Figure 3: (a) First image from the IR recording of the gear shown in

Figure 2 at a speed of 0.2m/s, and (b) thermal profile along the dotted line.

(a) (b)

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1 cm

0 20 40 60 80 100 120 1400

50

100

150

200

250

Dis tanc e along profile

Pix

el In

tens

ity

1 cm

0 20 40 60 80 100 120 1400

50

100

150

200

250

D is tanc e along pro file

Pix

el In

tens

ity

A more extensive on-line testing protocol allows us to conduct a statistical study over hundreds, even thousands of samples. This determines the repeatability of the testing and provides qualitative information about the stability of the background. A long IR image sequence of more than one minute (74 seconds) provides 2266 recorded temperature points with an intensity profile presented in Figure 6. As expected, whenever a part moves past the fixed spatial location, the temperature increases.

Figure 4: (a) Second image from the IR recording of the gear shown in

Figure 2 at a speed of 0.2m/s, and (b) thermal profile along the dotted line.

Figure 5: (a) Third image from the IR recording of the gear shown in

Figure 2 at a speed of 0.2m/s, and (b) thermal profile along the dotted line.

(b)

(a) (b)

(a)

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306

307

308

309

310

311

312

313

314

315

0 10 20 30 40 50 60 70

Time (Sec)

Tem

pera

ture

(K)

Figure 6: Temperature (K) recorded at a fixed spatial location (one spot) over time. A closer investigation of the data sequence reported in Figure 6 allows us to do conduct a more thorough analysis, as depicted in Figure 7. Here every temperature “spike” is equivalent to a gear tooth.

306

307

308

309

310

311

312

313

314

315

30 31 32 33 34 35 36 37 38 39 40

Time (Sec)

Tem

pera

ture

(K)

Figure 7: Zoomed-in temperature (K) recorded at a fixed spot location.

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The following images represent 2D surface and line profiles (recorded along the dotted line) captured with an IR camera positioned 50cm away (and viewed from the top) with similar settings as the recordings presented above.

1 cm

0 20 40 60 80 100 120 140 160 180

120

140

160

180

200

220

240

260

Distance along profile

Pix

el In

tens

ity

1 cm

0 2 0 4 0 6 0 8 0 1 0 0 1 2 0 1 4 0 1 6 0 1 8 01 2 0

1 4 0

1 6 0

1 8 0

2 0 0

2 2 0

2 4 0

2 6 0

D is ta n c e a lo n g p ro fi le

Pix

el In

tens

ity

Figure 8: (a) First image from the on-line IR recording of the gear part shown in

Figure 2 at a speed of 0.2m/s, and (b) thermal profile along the dotted line.

Figure 9: (a) Second image from the IR recording of the gear shown in

Figure 2 at a speed of 0.2m/s, and (b) thermal profile along the dotted line.

(b)

(a)

(a)

(b)

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1 cm

0 20 40 60 80 100 120 140 160 180120

140

160

180

200

220

240

260

D is tanc e a long p ro file

Pix

el In

tens

ity

The statistical analysis starts with a long-term data collection shown in Figure 11 and Figure 12; they present a more detailed view of the thermal profile over time.

308

309

310

311

312

313

314

315

316

317

318

0 10 20 30 40 50 60

Time (sec)

Tem

pera

ture

(K)

Figure 11: Temperature (K) recorded at a fixed spatial location (one spot) over time.

(a) (b)

Figure 10: (a) Second image from the IR recording of the gear shown in

Figure 2 at a speed of 0.2m/s, and (b) thermal profile along the dotted line.

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308

309

310

311

312

313

314

315

316

317

318

40 42 44 46 48 50

Time (sec)

Tem

pera

ture

(K)

Figure 12: Zoomed-in temperature (K) recorded at a fixed spot location.

CONCLUSIONS

Our preliminary thermal measurements during the manufacturing process (compaction) indicate that an IR inspection system can tolerate environmentally induced background radiation through image processing and a judicious choice of viewing angle adjustment and camera setting. We can conclude that an IR test system appears to be well suited for on-line inspection. Our present approach offers the ability to conduct a 100 percent testability of green-state compacts as they exit the compaction press. To accomplish a fully automated test system, more in-depth data analysis software needs to be implemented. The algorithm required would be based on the techniques presented in our previous reports, including thresholding, edge detection, and feature extraction.

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Report No. 05-#2 APPENDIX B ELECTROTHERMAL DEFECT DETECTION IN POWDER METALLURGY COMPACTS

Souheil Benzerrouk1,2, Reinhold Ludwig1,2 and Diran Apelian1

1Powder Metallurgy Research Center METAL PROCESSING INSTITUTE 2Department of Electrical and Computer Engineering,

Worcester Polytechnic Institute, Worcester, MA 01609

ABSTRACT. Faced with increasing market pressures, metal part manufacturers have turned to new processes and fabrication technologies. One of these processes is powder metallurgy (P/M), which is employed for low-cost, high-volume precision part manufacturing. Despite many advantages, the P/M process has created a number of challenges, including the need for high-speed quality assessment and control, ideally for each compact. Consequently, sophisticated quality assurance is needed to rapidly detect flaws early in the manufacturing cycle and at minimal cost. In this paper we will discuss our progress made in designing and refining an active infrared (IR) detection system for P/M compacts. After discussing the theoretical background in terms of underlying equations and boundary conditions, analytical and numerical solutions are presented that are capable of predicting temperature responses for various defect sizes and orientations of a dynamic IR testing system. Preliminary measurements with controlled and industrial samples have shown that this active IR methodology can successfully be employed to test both green-state and sintered P/M compacts. The developed system can overcome many limitations observed with a standard IR testing methodology such as emissivity, background calibration, and contact resistance. Key words: Active infrared imaging, P/M compacts, dynamic temperature recording. PACS: 81.70Ey, 41.20.Cv, 44.05.+e, 44.40.+a, 02.60.Cb, 02.70.Dh, 07.57.Ty, 61.43.Gt

INTRODUCTION

In an effort to extend IR detection to P/M compacts, we have explored pulsed thermography whereby the sample is excited with a current pulse and the thermal response is recorded over time. This will enhance the detection capabilities to include subsurface defects and relatively small surface breaks. Due to the complex nature of the thermo-electric phenomena, numerical modeling will be extensively used to study the thermal response of un-flawed and flawed samples subject to electric excitation. Specifically, during this phase of investigation we will at first explore a steady state approach followed by a more elaborate transient analysis. As part of a general performance evaluation of the IR approach, testing was conducted with controlled samples of different material compositions.

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ANALYTICAL FORMULATION

To develop a comprehensive theoretical modeling formulation of the IR inspection system, three coupled physical models must be investigated: electrostatics, thermal, and heat radiation. In particular, the following systems are identified: A) the electric heat source generation and its electro-thermal coupling, B) the heat distribution over the compact’s surface, including mechanisms that take into account ambient effects, and C) the imaging system that records all sources of IR radiation as well as optical effects of the P/M parts.

Heat Source: Steady State and Transient Current Excitations Electric energy is coupled into the P/M sample through surface contacts acting as electrodes. This energy is induced in the form of direct current (DC) or transient current flow, which will establish a voltage distribution throughout the part. The voltage distribution in a P/M part with spatially dependent conductivity is governed by Laplace's equation in the form

Here ( )zyx ,,σ is electric conductivity of the medium and ( )zyx ,,Φ is the voltage distribution in the sample.

Voltage Response and Flaw Representation To provide insight into the voltage-defect interaction inside a P/M compact, we can approximate the flaw as a sphere with conductivity and dielectric properties ( dd εσ , ) that are different from the bulk properties of the P/M compact ( SS εσ , ). The applied voltage excitation via the electrodes establishes an electric field )(tE throughout the compact. This electric field is assumed to be uniform in the absence of the spherical defect; this results in a linear voltage gradient. If a spherical defect of size R is embedded into the samples as shown in FIGURE 13, both the electric field and potential distribution are perturbed [11]. According to classical potential theory, Laplace’s equation in spherical coordinates outside the sphere r > R assumes the classical dipole voltage

Here ( )tA is a time dependent coefficients that can be determined by solving the initial value problem under the assumption that the imposed electric field is switched on via a step function (h(t)=1, if 0≥t , and 0 if 0<t ), i.e. ( ) ( )thEtE 0= . The final solution in a spherical coordinate system (see Figure 3) takes on the form

[ ] 0),,( =Φ∇⋅∇ zyxσ (1)

( ) Rrr

tAd >=Φ ;cos2θ (2)

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Ζθ

R

Ε ( t)

r

FIGURE 13. Spherical defect subjected to a time varying electric field. As stated above, sε and sσ are the permittivity and the conductivity of the sample and dε and dσ are the permittivity and the conductivity of the spherical defect. Here the relaxation time τ in (3) is defined as

In general, (4) suggests for P/M compacts ( 3,

12, 10,10 ≈≈ −

dSdS σε ) that the relaxation time is negligibly small; thus the exponential term in (3) can be discarded. Consequently, the total potential outside of the spherical defect is the sum of the applied voltage distribution through the sample, )(0 tzhEa −=Φ , and the dipole voltage. As a result, for r > R we can determine the total voltage as follows

Here, dVE /00 = is based on the 1-D capacitor model with the voltage 0V measured at the electrodes over the length of the sample d. The total electric field E throughout the P/M sample (and outside of the spherical defect) is computed as the gradient

From the electric field one can then determine the power density deposited in the compact

( ) )(2

12

cos2

3

0 theerRE t

ds

dst

ds

sdd ⎥

⎦

⎤⎢⎣

⎡+−

+−+−

−=Φ −− ττ

εεεε

σσσσθ (3)

ds

dsσσεε

τ++

=22

(4)

)(2

cos)(cos 2

3

00 thrREthrE

ds

sd⎥⎦

⎤⎢⎣

⎡+−

−−=Φσσσσθθ (5)

Φ−∇=E (6)

22),,,( Φ∇== dd EtzyxQ σσ (7)

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Temperature Distribution Since the dominant transfer mechanism in P/M compact testing is heat conduction, we can cast the thermal equation as

with the parameters denoting the density of the material ρ, the heat capacity c, the thermal conductivity k, and the active heating power source Q as given in (7).

FEM FORMULATION

To theoretically investigate the applicability of the IR imaging technique for the detection of surface-breaking cracks and subsurface defects, it becomes necessary to first evaluate the temperature changes and ensure that they fall within the detection limits of the IR imager with reasonable margins. The defects shown in FIGURE 14 (a) are voids with the following thermo-physical properties: material density of ρ = 1.18 kg/m3, electrical conductivity of σ = 35 x 10-15 S/m, heat capacity of c = 1005.7 W/kg°C, and thermal conductivity of k = 0.026 W/m°C. The simulated flaws have the following dimensions: Flaw 1: 100 μm wide by 20 μm deep, embedded 1cm below the surface; Flaw 2: 20 μm wide by 20 μm deep, surface breaking, and Flaw 3: 1000 μm by 500 μm deep, also surface breaking. As seen in FIGURE 14, the surface-breaking cracks appear detectable. However, the resulting temperature signature varies with flaw size and orientation. Interestingly, subsurface defects do not produce a detectable temperature gradient over the surface under steady state electric excitation conditions. Consequently we have to extend the thermal analysis to a transient formulation.

(a) (b) FIGURE 14. Temperature distribution in a flawed compact (a), and surface profile along the z-axis (b).

( ) QtTcTk −∂∂

=∇⋅∇ ρ (8)

Flaw 1

Flaw 2

Flaw 3

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Dynamic Modeling Dynamic electro-thermography offers a number of significant advantages, including the possibility to detect subsurface defects and very small surface-breaking defects. The resulting predictions in FIGURE 15 show a distinguishable signature from a small surface break and a noticeable temperature change, clearly indicating the presence of a defect.

FIGURE 15. Temperature profile (in K) recorded (in m) along the surface of a compact for three different time instances of 2, 5, and 10 s.

EXPERIMENTAL STUDY

Our experimental study focused initially on capturing static thermal images of green-state compacts with surface cracks subject to DC current excitation. In a second step our study was extended to create an environment for controlled dynamic testing. Here the parts with subsurface defects are subjected to a current step (or pulse) of a specific shape. The current injection is triggered by the same computer command used to activate the camera recording, and hence synchronize the heating with the image acquisition. The practical IR system is depicted in FIGURE 16.

FIGURE 16. Practical IR test arrangement showing the camera, the contacts and the switching circuit.

Press

Painted P/M part

IR camera

Switching circuit

Control computer

DC Power

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Static Imaging In an effort to evaluate the effects of flaw size, shape, and orientation, a number of defects were artificially created.

These defects were created in a cylindrical part consisting of 1000B powder without lubricant. The compact is then subjected to a DC current flow of 20A.

FIGURE 17. IR image recording from a cylindrical green-state compact with four artificially created surface-breaking defects.

A Matlab program was written to set an intensity threshold and convert the image into a "binary" representation. In other words, a two level representation is adopted where all pixels whose values reach or exceed a predefined threshold value are assigned to the "bright" bin whereas pixels with values below the threshold value are assigned to a "dark" category. FIGURE 18 represents the previous IR image after thresholding.

(a) (b)

FIGURE 18. (a) IR image of the cylindrical part after thresholding, and (b) profile along the centerline with a spatial pixel-to-pixel distance of 300 μm.

Dynamic Imaging The parts tested here are rectangular in shape with dimensions of: 3.175cm x 1.27cm x 1.27cm. The material used in making the samples is FC-0205 which is a mixture of Iron, 2% Copper and 0.5% Carbon. The same number of parts was tested with 0.55% EBS lubricant or die wall lubrication (DWL). For the purpose of observing the influence of density on the heating, the tested samples were compacted to various densities: 6.6 g/cm3, 6.9 g/cm3, and 7.2g/cm3. The test also included finished parts where we tested a similar set of compacts after sintering.

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(a) (b)

(c) (d)

FIGURE 19. IR recording at, (a) t = 0sec., (b) t =2 sec., (c) t = 15sec., (d) t = 25.

On-Line Testing The following IR images represent 2D surface and line profiles (recorded along the dotted line) recorded with an IR camera positioned 50cm away and operated at a frame rate of 30Hz. The field of view of the 240 by 320 pixels is 15cm by 15cm. The total line length of 10cm is subdivided into 180 equally spaced points. A practically useful processing technique is the selection of an area or a spot in the manufacturing line where the temperature can be tracked over time. The thermal profile, as seen in Figure 8, permits the study of part density uniformity as well as part-to-part process repeatability.

FIGURE 20. (a) Image from the on-line IR recording of a cylindrical part at a speed of 0.1m/s, and (b) thermalprofiles along the dotted line of three consecutive parts.

(a) (b)

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300

305

310

315

320

325

330

335

340

345

0 5 10 15 20 25 30 35

Time (sec)

Tem

pera

ture

(Deg

ree

K)

CONCLUSIONS

The primary objective of this work is to establish the suitability of IR imaging for the detection of defects in green-state P/M compacts in an industrial setting where a number of environmental radiation sources compete with the natural response of the P/M part. The second objective is to experimentally confirm the ability to detect subsurface defects dynamically, which requires the design of a control system to synchronize and monitor the thermal responses. Preliminary testing revealed that pulsed thermography can successfully be employed to detect subsurface defects in green-state parts. This conclusion agrees with our numerical predictions based on extensive finite element modeling efforts. We can conclude that an IR test system appears to be suitable for on-line inspection, hence providing the ability to conduct 100 percent testability of green-state compacts as they exit the compaction press. Although the data presented in this paper is encouraging, a fully manufacturing compliant IR test system requires more in-depth analyses encompassing different industrial settings such as various part geometries, densities, and part velocities. Furthermore, artificially created defects embedded in the samples are needed to observe the sensitivity of the IR image acquisition.

FIGURE 21. (a) IR recording of the part with respect to a fixed spatial location.(b) Temperature (in K) response recorded for three moving P/M parts.

(a) (b)

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REFERENCES

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2. Fei, M. "Electromagnetic Inspection, Infrared Visualization and Image Processing Techniques for Non Metallic inclusions in Molten Aluminum" Master Thesis, ECE Department, Worcester Polytechnic Institute 2002.

3. Maldag, X.P.V. "Theory and Practice of Infrared Technology for Nondestructive Testing" John Wiley & Sons Inc. 2001.

4. Carslaw, H., Jaeger, J. "Conduction of Heat in Solids" Second Edition, Oxford University Press 1959.

5. Incropera, F.P., DeWitt, D.P. "Fundamentals of Heat and Mass Transfer" 4th edition, John Wiley & Sons, New York 1996.

6. Kraus, J.,D. "Electromagnetics" McGraw-Hill Book Company, Inc. 1953. 7. Ringermacher, H.I., Howard, D.R. and Gilmore, R.S., "Discriminating Porosity in

Composites Using Thermal Depth Imaging" Review of Progress in QNDE, Vol. 21, 2002.

8. Han, X., Favro L.D., and Thomas, R.L., "Recent Developments in Thermosonic Crack Detection" Review of Progress in QNDE, Vol. 21, (2002).

9. Sun, I.G "Analysis of Quantitative Measurements of Defects by Pulsed Thermography Imaging" Review of Progress in QNDE, Vol. 21, (2002).

10. Hausseker, H.W “Simultaneous Estimation of Optical Flow and Heat Transport in Infrared Image Sequences” IEEE Conference on Computer Vision and Pattern Recognition 2000.

11. Hermann A. Haus/James R. Melcher “Electromagnetic Fields and Energy “Prentice-Hall Inc., New Jersey. 1989.

12. Powder Metallurgy Research Center (PMRC), Metal Processing Institute, Worcester Polytechnic Institute, fall meeting, Oct. 20, 2004.