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

PM Compacts

Report No. PR-07 - #1

OBJECTIVE The objective of this research is the development of an infrared system for the detection of defects in P/M compacts. The system targets the ability to provide one hundred percent evaluation at the compaction stage. This enables the most cost effective process monitoring and control. Our completed theoretical model provides the foundation and calibration for all relevant system parameters. In particular, the finite element modeling sets minimum detectable limits for both sub-surface and surface defects. A custom software package was developed that acquires, processes, and analyses IR images; it provides feedback in an intuitive display format of the IR images along with pass/fail messages for the operator.

The milestones identified by our focus group members for this final project period encompass:

a) Completion of the custom software package that interfaces with the hardware environment of the IR camera system. It is based on two options:

1. Simple pass/fail feedback for the machine operators during in-process

operation of the IR system.

Research Team: Reinhold Ludwig (508) 831-5315 ludwig@wpi.edu Souheil Benzerrouk (508) 831-6797 souheil@wpi.edu

Focus Group Members:

Chaman Lall Metal Powder Products, Chair Richard Scott Nichols Portland Michael Krehl Sinterstahl Hannes Traxler PLANSEE Aktiengesellschaft

2. Comprehensive data visualization and analysis for a more in-depth failure

study.

b) Completion of the patent application 30210-121 with USPTO through PMRC/WPI. This effort will be completed in June.

APPROACH The PMRC focus group members identified three major tasks to be conducted during the Fall 2006 - Spring 2007 time period. Specifically, emphasis has been placed on:

• Implementing our data analysis algorithm to perform advanced image analysis of the green-state compacts,

• Extensive testing of the custom software package in a lab setting and possible in a

manufacturing environment

• Filing for a provisional patent to protect the developed intellectual property. ACCOMPLISHMENTS For this final reporting time period, the researchers can report the following accomplishments:

• Completion of the custom software package for on-line testing relying on the residual heat convection as the compacts exit the press system.

• Implementation of specialized features for off-line testing that exploit external

heating mechanism (direct current, induction) to create a controlled temperature rise in the compacts.

• In-house testing of the custom-developed software.

• Extension of the theoretical formulation to study the effect of diffusion on the

thermal signature arising from a defect.

• Conversion of the provisional patent to a utility patent with US designation (effort should be completed in June).

REPORT ORGANIZATION

Appendix A – Contains a paper submitted to the IEEE to be published in the Transactions of Measurements and Instrumentations Appendix B – Contains a paper that was presented at the International Conference on Powder Metallurgy and Particulate Materials, PowderMet07 Denver, CO, May 13-16 2007. ACKNOWLEDGEMENT We would like to thank our focus group members for their guidance and their important technical input throughout this project period. In particular, we would like to thank Dr. Chaman Lall (Metal Powder Products) and Richard Scott (Nichols Portland) for their help and invaluable insight. Report No. 06-# 2 APPENDIX A

INFRARED EVALUATION OF POWDERMETALLIC COMPACTS

Abstract — This paper discusses a novel approach to a full quality assessment of powder metallurgy (P/M) parts in the pre-sintered manufacturing process. The method is based on an active thermography approach that utilizes electric energy to induce heating throughout the metallic compact. Infrared (IR) images are collected and analyzed in an effort to yield part integrity and process stability information. In this paper we will discuss our design approach, the theoretical modeling aspects, and a proof-of-concept instrument with associated data processing software.

As part of our experimental data processing, we will present results collected both in a laboratory setting and in an industrial manufacturing environment. The P/M sample analyses are done through a custom software package.

Index Terms—Nondestructive evaluation, infrared imaging, powder metallurgy, active thermography, component testing.

INTRODUCTION OWDER metallurgy is a manufacturing method where precision metal parts are produced by compressing metal powder at high pressure. The resulting compacts are of high dimensional fidelity

and possess low strength due to limited bonding between the powder particles; hence the requirement of a subsequent processing phase that involves sintering. Here the compacts are heat treated at elevated temperature over a prolonged time period to create high strength parts. Because of low-cost manufacturing these compacts find wide ranges of applications such as the automotive sector where quality, volume, and price are of equal importance 1, 2.

The P/M manufacturing process has unique quality assurance requirements, largely due to the fact that

failure mechanisms are different from parts fabricated by other metalworking techniques. Ideally, the quality assessment should be non-intrusive, high-speed, and conducted at the lowest possible cost. It is desirable to administer NDE tests as early as possible in the production cycle. Unfortunately, a review of currently employed NDE techniques has shown that most of the classical testing methods cannot directly be applied to the metal-powder industry without major modifications 3. This is particularly true for the early evaluation in the manufacturing process: the pre-sinter, or green-state, condition where the parts are still ductile.

Despite concerns with existing NDE techniques, it was reasoned that a modified IR-based inspection

approach may prove suitable to meet both rapid inspection and minimum intrusion requirements for a wide range of single level and multi-level compacts. Our proposed system is capable of testing green-state compacts based on a thermo-electric approach. We use electric current as a heating source (Joule heating) because of its low cost, controllability, and simplicity to deploy. The electric current, due to the finite conductivity of the compacts, creates a power loss that translates into a temperature rise on the surface of the sample. The thermal signature is then recorded through an infrared camera. To detect embedded defects such as cracks or inclusions we can take advantage of the transient temperature response when the compact

S. Benzerrouk and R. Ludwig are with the Electrical and Computer Engineering Department, and D. Apelian is with the Mechanical Engineering Department, Worcester Polytechnic Institute, Worcester, MA 01609 USA, (e-mail: souheil@wpi.edu).

S. Benzerrouk (Student Member), R. Ludwig (Senior Member), and D. Apelian

P

is exited by, for instance, a step function of current.

In general, a complete theoretical modeling approach would include complex, nonlinear temperature related feedback mechanism of the material parameters. In this paper, however, only the forward solution is studied, i.e. the direct energy transfer mechanisms between the electrical and thermal models.

Moreover, due to the complex nature of the thermo-electric phenomena, numerical modeling will be extensively used to study the thermal response of unflawed and flawed samples subject to electric current excitation. In particular, the simulations will involve 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.

THEORETICAL ANALYSIS

To develop a theoretical model that can serve as a testbed for the IR inspection system, the physical phenomena of Joule heating, heat transfer, and IR radiation have to be included. In particular, we have to isolate the following theoretical systems: A) the electric heat source with electro-thermal coupling, B) the heat distribution over the surface with ambient effects, and C) the imaging system that records all sources of IR radiation as well as optical effects emanating from the green-state P/M compacts.

Heat Source Electric energy is coupled into the sample through surface contacts acting as electrodes. The injected

electrical current I will establish a voltage distribution throughout the part; the resulting electric field and the associated material conductivity will give rise to power deposition consistent with Joule’s law 11, 5.

Applying a constant current source to the P/M specimen can be accomplished by placing the compact

between two electric contacts as shown in Fig. 1. The purpose of the enlarged contact area is to reduce boundary effects due to charge build up and to ensure uniform current flow throughout the part.

The voltage distribution V(x,y,z) in the part with spatially dependent conductivity σ (x,y,z) is governed by

Laplace's equation in the form:

[ ] 0),,( =!"! Vzyx# (1) This equation can only be solved analytically for canonical geometries 6; however, closed-form solutions

cannot be obtained for complex, multi-level P/M industrial compacts such as gears. Nonetheless, controlled samples can easily be pressed into cylindrical shapes with approximately constant conductivity. For this

DC Source

Sample

Under test

Contact

terminals

I

!

Fig. 1. Cylindrical P/M part of conductivity! placed between electrical contacts and subjected to a constant current flow I.

case, (1) can be restated in cylindrical coordinates ( r ,! , z ) as:

011

2

2

222

2

=!

!+

!

!+

!

!+

!

!

z

VV

rr

V

rr

V

"

(2)

Employing the separation of variable approach for a cylinder of length 2L and radius R and imposing a constant voltage V0 at the top and ground at the bottom, yields the solution 11

( )( ) ( )( ) ( )!

"

=

=1 1

00

sinh

sinh2,

n nnn

nn

LRJ

rrJ

R

VzrV

###

## (3)

In (3), J0(…) and J1(…) are Bessel functions of zeroth and first order and γn is defined in (8) below. The injected electric current deposits power throughout the part due to the finite conductivity in the

sample. The power per unit volume Q is described by Joule’s law: 222

/ VEJQ !=== """ (4) where J and E are, respectively, current density and electric field.

Temperature Distribution Since the dominant transfer mechanism in our proposed testing technique is heat conduction, we can

state the heat equation as 7, 8:

Qt

Tc

z

T

r

Tr

rr

k!

"

"=

"

"+#$

%&'

(

"

"

"

")

2

2

(5)

Here the parameters denote density of the material ρ, heat capacity c, thermal conductivity k, and heating power Q as defined in (4). Under steady state condition, (5) simplifies to

Qz

T

r

Tr

rr

k!=

"

"+#$

%&'

(

"

"

"

"2

2

(6)

Here again, an axis-symmetric solution can be developed by an orthogonal series expansion of the form

[ ]!"

=

#$

%&'

(

+

+)

=

1

0

042

3

)(])/(1[

)/cosh(/)/tan(

)/cosh()/(1

2),(

n

n

nnn

nnn

nn

R

rJ

JhR

RLhRRL

RzhR

k

QhRzrT

*

***

***

**

(7)

Where h is the convection heat transfer coefficient, k represents the thermal conductivity, and n! are the positive roots of the transcendental equation:

)()( 01 nnn

RhJJ !!! = (8)

An example solution was computed for the following parameters representing a green-state P/M compact

prepared by GKN, Inc. Worcester, MA:

• Radius: R = 0.005 m • Length: 2L = 0.06 m • Heating Power: Q = 767 kW/m3 • Thermal conductivity: k = 25 W/m°C

• Convection heat transfer coefficient: h=10 W/ m2°C

Fig. 2. illustrates the numerically predicted temperature distribution throughout the compact. As expected, the temperature is at a maximum in the center and decays to a minimum value along the surface due to convectional cooling.

Defect Modeling A defect is modeled as a discontinuity in the material and is regarded as either a source or a sink of energy depending on the electric energy deposition. To capture the impulsive thermal response, we can employ the method of images. This concept is based on creating a point source in the plane normal to the plane of symmetry [24], as depicted by Fig. 3.

The corresponding thermal impulse response G(x,y,t), or the Green’s function solution, can be written as follow:

Fig. 2: Color coded distribution of the temperature rise in °C for a cylindrical compact of 6cm in length and 1cm in diameter.

Image

x

y

Defect

Imaged surface

of the P/M part

Convective

boundary

Fig. 3. Idealized sub-surface defect representation as an embedded point source.

( )

( ) ( )

!!!

"

#

$$$

%

&

++'+

'+'=

++''

'+''

22

4

)'()'(

22

4

)'()'(

3 )'()'()'()'(

1

2222

yyxx

e

yyxx

e

tG

t

yyxx

t

yyxx

((

)

(9)

Here (x, y) indicate a spatial point in the simulated half-space, (x’,y’) denote the defect coordinates, ! is the thermal diffusivity, and t is the time.

Fig. 4. depicts the temperature increase (G) over time and the length in the x-direction on the surface of

the part (y=0) for the following parameters:

• Part surface Length: 10cm • Defect location: (x, y)=(5cm,5cm) • Heating power: Q=8 Watts

FINITE ELEMENTS MODELING Due to the complex nature of the electro-thermal interaction for complex P/M shapes, especially in the

inhomogeneous case where sources or sinks are present, finite element (FE) analysis is used to predict the temperature distribution over the surface of the compact. The FE analysis is also employed to define the power requirements needed to raise the part to the desired temperature range and help establish the camera specifications such as resolution and sensitivity. The numerical analysis in turn was tested through the analytical study developed above.

First an electrostatic model of a 3D cylinder was created with uniform conductivity. We define the

following parameters Length of P/M cylinder: mL 05.0= Radius of P/M cylinder: mR 01.0= Electrical conductivity: mS /105

4!="

which reflect practical sample values, as prepared by GKN, Inc. (Worcester, MA). The heat transfer model utilizes the following approximate parameters for the green-state P/M compacts: ρ = 7250 kg /m 3 c = 440 W/kg °C k = 40 W/m °C h = 10 W/ m 2 °C

0

2

4

6

8

10

-10

-5

0

5

10

0

10

20

30

40

50

60

Time (s)

Surface length (cm)

Temperature rise (K)

5

10

15

20

25

30

35

40

45

50

55

Fig. 4. Temperature rise over the compact’s surface due to an embedded heat source.

The boundary condition is set to be of Neumann type, i.e., flux free. Fig. 5 depicts a 3D numerical simulation of the temperature distribution throughout the cylindrical compact.

Static Modeling

To validate the applicability of the IR imaging technique for the detection of surface cracks and internal

defects, it is necessary to first evaluate the temperature changes and ensure that they fall within the detection limits of our imager with reasonable margins. The theoretical defect sizes that should be considered are on the order of 20µm, which can result in extensive computations. However, a 2D representation of surface and near-surface defects appears sufficiently adequate.

This analysis is subdivided into two sections: the first focuses on the steady state condition, where no

time component is included. The second section extends the previous model to include transient effects and consequently estimate the response time of the technique.

The simulated three defects are shown in Fig. 6. with the dimensions of 20µm by 100µm situated 1.5

mm below the surface (Flaw 1), 100µm by 20µm situated on the surface (Flaw 2), 500µm by 1000µm also on the surface (Flaw 3). The defects have the following thermo-physical properties:

• Material Density: ρ = 1.18 kg/m3 • Electrical conductivity: σ = 35 x 10-15 S/m • Heat capacity: c = 1005.7 W/kg°C • Thermal conductivity: k = 25 W/m°C

Fig.5. Numerically predicted temperature distribution in K in an unflawed cylindrical compact; all dimensions are given in [m].

As seen in Figure 6, the surface cracks are clearly detectable and the resulting temperature signature

varies with flaw size and orientation. Interestingly, the subsurface defect does not produce a detectable temperature gradient on the surface under steady state electric excitation conditions. Consequently we need to extend the thermal analysis to a transient electric excitation condition.

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 transient numerical predictions with the same physical parameters are reported in Fig. 7. and show after 5 seconds a distinguishable signature of all three defects, including the small subsurface defect (Flaw 3) which is not noticeable in the static response. The response after 10 seconds approaches the static response of Fig. 6(b) when displayed on the same temperature scale.

0

0.005

0.01

0.015

0.02

0.025

0.03

0.035

0.04

0.045

0.05

364.9 364.95 365 365.05 365.1 365.15 365.2 365.25 365.3 365.35 365.4

L

e

n

g

t

h

[

m

]

Temperature [K]

Defects' signatures

(a) (b) Fig. 6 Temperature distribution in Kelvin of a simulated compact with (a) three types of flaws, and (b) surface temperature profile along the z-axis.

EXPERIMENTAL ANALYSIS

The experimental study focuses at first on capturing static and dynamic thermal images of green-state compacts subject to DC current excitation. This step enables us to establish a measurement baseline that includes radiation effects from the surrounding. Second, the static and dynamic IR imaging is then deployed for the detection of surface defects within the green-state parts. However, a complete detection system requires two additional components: a graphical display whereby the captured thermal image is visualized, and an image processing and evaluation algorithm that is related to assessing the integrity of the sample from the constructed image. Here, basic image analysis techniques such as profiling and thresholding are employed. The complete detection system includes at its heart a camera with a spectral range of 8-12 µm that is capable of detecting absolute compaction temperatures of up to 700C and a minimum temperature difference of approximately 0.1°C as suggested by Fig. 6(b).

Static IR Detection and Image Processing In an effort to evaluate the effects of flaw size, shape, and orientation, a number of defects were

artificially created. Using an exacto knife, surface-breaking defects were produced with approximate dimensions as listed in Table 1.

TABLE 1 APPROXIMATE FLAW PARAMETERS IN GREEN-STATE CYLINDRICAL PARTS (THE LOCATION IS DEFINED AS DISTANCE FROM THE PART

SURFACE).

Flaw #

Length [mm]

Width [µm]

Depth [µm]

Orientation Location [cm]

1 10 <20 <20 Horizontal 1 2 1 20 20 Horizontal 2 3 2 20 20 Vertical 3 4 10 <20 <20 Vertical 5

0 0.005 0.01 0.015 0.02 0.025 0.03 0.035 0.04 0.045 0.05300

302

304

306

308

310

312

Length [m]

T

e

m

p

e

r

a

t

u

r

e

[

K

]

t = 5 sec.

t = 10 sec. t = 2 sec.

Fig. 7. Transient temperature profile in Kelvin over the surface (scale in [m]) of a compact recorded at three different time instances of 2, 5, and 10 seconds.

These defects were created in a cylindrical P/M compact consisting of 1000B powder without lubricant. The sample is then subjected to a DC current flow of 20A. Next, an IR image was acquired, stored in a PC, and post-processed by setting a threshold. Figure 8 illustrates the IR image taken from the part prior to any processing. The image is recorded in an index image format, which is transformed in the camera to a gray-scale. It takes the form of an intensity matrix where the value of each pixel is in the range from 0 to 255. The elements in the intensity matrix represent gray levels with 255 representing full intensity 9, 10, 11. This image is later paletted for viewing using a simple coloring scheme where the base temperature is encoded in green, cooler areas are represented in blue, and hot spots are displayed in red.

To quantify the temperature gradient caused by the presence of defects, we generated a thermal line

profile precisely intersecting the area of interest. Fig. 9. depicts the image profile along a line that traverses across all defects (line 2) and a profile (line 1) that is parallel to line 2, but with a 5mm offset in order to profile a flawless line.

A computer 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 in which all pixels whose values reach or exceed the threshold value are assigned to a "bright" category. Pixels with values below the preset value are assigned to a "dark" category. To display the image in a more comprehensive manner a more elaborate scheme can be devised: here the image with threshold is used to identify the “dark” pixels only and assign them a “0” value, while maintaining intensity values of all other pixels. Fig.10 represents the IR image of Fig. 8 after signal processing. As one can observe, the artifacts associated with the density variation in the interior of the compact can be eliminated, while the current injection points on the upper and lower portions

Fig..8. IR image recording from a cylindrical green-state compact with four artificially created surface-breaking defects.

Fig. 9: Thermal profiles over 200 pixels along two dotted lines depicted in Fig. 8; the spatial pixel-to-pixel distance is 300µm.

of the compact are made more pronounced.

The results presented in this section show that sizeable flaws can readily be detected through a steady state test arrangement. However, as demonstrated in the theoretical modeling section, very small surface cracks and subsurface defects cannot be detected; they require a dynamic test arrangement.

It is also apparent from the images shown that there is a discrepancy between the numerical modeling

and the experimental results. This difference is largely due to the fact that in the theoretical analysis certain artifacts of the powder-metallurgy process as well as the evaluation method are not taken into account. For instance, in the study the density (and hence the conductivity) was assumed uniform. However, in practice this assumption is not valid; indeed, it is dependent on the way the powder is compacted 1. For the case of a cylindrical compact the density is lower at the top and bottom if the press is a dual punch type (pressure is applied to both ends). Another factor that results in higher temperature rise at the top and bottom extremities of the compact is due to the contact resistance. DC heating, although very predictable and controllable, has the drawback of inducing additional heating at the compact/electrode interface. As demonstrated above, this problem can be resolved through appropriate image processing.

The gears shown Fig. 11, present two typical difficulties encountered owing to their geometric

arrangement. First, the gear teeth cause non-uniformity in the part, which in turn causes reflections. Second, the multilevel nature of the part makes it prone to corner cracks which cannot easily be detected as a result of complicated heat transfer mechanisms at the corner.

(b)

Fig. 10. (a) IR image of the cylindrical compact after thresholding, and (b) profile along the centerline with a spatial pixel-to-pixel distance of 300µm.

These steel powder compacts are constructed with 1.0% Cu, 0.2% C and lubricated with 0.8% wax. The

density ranges from 6.8 g/cm3 to 7.1 g/cm. These defects are not easily detectable if the source of heating is direct current (DC) because it requires

high current density and additional electrode contacts to ensure uniform current flow throughout the part. An improved inspection approach utilizes an AC current excitation where the frequency of the source dictates the depth of current penetration. This approach will ensure that the current flows on and near the surface of the part, hence increasing the thermal signature of the defect to a detectable level.

Fig. 12 depicts the test arrangement; it utilizes an induction-heating unit consisting of a power supply

and an induction coil suspended below the compact, which renders the technique contact-less.

Fig. 13 displays IR images for 2D surface and line profiles (along the dotted line). The data is collected 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 pixel picture 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 up to a maximum discrete level of 260 (or 460K).

Fig.12. Contact-less test arrangement of active IR testing unit.

Fig.11 A gear compact with a surface crack situated on the tooth surface.

It is clear from Fig. 13 that the crack is easily discernable when one uses induction heating rendering the analysis simple and reliable.

Another important component of our system is the signal processing. We apply several mathematical tools to extract defect information from the image. Specifically, we analyze the derivative of the thermal profiles on the surface of the compact.

Conclusion This paper introduces a novel IR evaluation system for the detection of defects in P/M compacts. It also

develops the analytical formulations and numerical solutions such that basic system calibration can be assessed. The basic premise is to inject DC or AC current through the compact to create a temperature gradient that will subsequently be captured by An IR camera.

A mathematical model was developed where the voltage and temperature distributions can be predicted throughout the volume of the P/M parts subject to a current input. The model is based on DC current injection prescribed over a finite aperture of the part geometry. We also modeled the defect as a point source through the method known as the method of images. Other defect shapes can easily be extrapolated from the point source through integration. Thereafter, the numerical model is tested against an analytical solution of a cylinder. This permits the prediction of current versus temperature behavior needed to select appropriate camera settings. Finally, the computational approach was extended to include an analysis related to the detection of thermal radiation emanating from the target as well as the surroundings, while taking into account the reflection caused by the P/M compact.

The long-wavelength IR camera system together with the power supply and data analysis software

constitutes the basic testing prototype that enables us to conduct a number of controlled experiments. Specifically, steady state tests reveal that surface cracks on the order of 20 microns can be detected. While transient testing allowed the detection of smaller cracks and defects embedded under the surface of the part. With additional signal processing steps it appears feasible that a fully automated evaluation system is possible on the factory floor. Although we have not yet tested compacts with subsurface cracks, the dynamic test with a pulsed current excitation such as a step function should enable us to extend the capability of this IR system to detect defects situated below the surface.

ACKNOWLEDGMENT We would like to extend our gratitude and thanks to the members of the Powder Metallurgy Research

Center (PMRC) at WPI for their guidance and their valuable inputs throughout this project. Especially, we would like to thank Richard Scott (Nichols Portland), Dr. Ian Donaldson (GKN Sinter Metals, Worcester) and Dr. Chaman Lall (Metal Powder Products) for providing the facilities to complete our on-line testing, for the samples they supplied and their insightful inputs.

1 cm

0 10 20 30 40 50 60160

170

180

190

200

210

220

230

240

250

260

Distance along profile

Pixel intensity

(a) (b)

Fig.13. (a) Initial image from the IR recording of the defective gear part shown in Fig.11 (a), (b) thermal profile along the dotted line.

REFERENCES 1. German, R.M., Powder Metallurgy Science, Metal Powder Industries Federation, Princeton, New Jersey, 1984. 2. Clark, F., Advanced Techniques in Powder Metallurgy, Rowmann and Littlefield Inc. New York, NY 1963. 3. Leuenberger, G. "Electrostatic Density Measurement in Green-State P/M Parts" PhD thesis, ECE Department, Worcester

Polytechnic Institute 2003. 4. Kraus, J.,D. , Electromagnetics, McGraw-Hill Book Company, Inc. 1953. 5. Bruhat,G. , Cours De Physique Général: ELECTRICITE, Septième Edition, Masson & Cie . 1959. 6. Gochenbach, M., S., Partial Differential Equations: Analytical and Numerical Methods, Society for Industrial and Applied

Mathematics, 2002. 7. Carslaw, H., Jaeger, J., Conduction of Heat in Solids, Second Edition, Oxford University Press 1959. 8. Incropera, F.P., DeWitt, D.P., Fundamentals of Heat and Mass Transfer, 4th edition, John Wiley & Sons, New York 1996. 9. 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. 10. Maldag, X.P.V. "Theory and Practice of Infrared Technology for Nondestructive Testing" John Wiley & Sons Inc. 2001. 11. Burnay, S. G., Williams, T. L., Jones C. H., Applications of Thermal Imaging, P Publishing Press 1988. 12. Logan, D. A., First Course in Finite Elements Method, PWS Publishing Company 1993. 13. Ringermacher, H.I., Howard, D.R. and Gilmore, R.S., "Discriminating Porosity in Composites Using Thermal Depth

Imaging" CP 615, Review of Quantitative Nondestructive Evaluation, Vol. 21, ed. by Thompson and D.E Chimenti. American Institute of Physics. 2002.

14. Han, X., Favro L.D., and Thomas, R.L., "Recent Developments in Thermosonic Crack Detection" CP 615, Review of Quantitative Nondestructive Evaluation, Vol. 21, ed. by Thompson and D.E Chimenti. American Institute of Physics. 2002.

15. Sun, I.G "Analysis of Quantitative Measurements of Defects by Pulsed Thermography Imaging" CP 615, Review of Quantitative Nondestructive Evaluation, Vol. 21, ed. by Thompson and D.E Chimenti. American Institute of Physics. 2002.

Souheil Benzerrouk (M’00-S’04) received his diplome d’ingenieur d’etat from the university of Blida, Algeria in electronics in 1996 and the M.S. degree in Electrical Engineering from Worcester Polytechnic Institute in 2004. Currently he is a research assistant and a PhD candidate in the electrical and computer engineering of Worcester Polytechnic Institute, his research focus has been the development of process instrumentation and the numerical modeling of electrostatics and electromagnetics applied to nondestructive evaluation of materials. From 1998-2006, He was involved in the development of process instrumentation, medical equipment, and switching power supplies for solid-state lasers and plasma reactors in the industry. Among the companies he worked for; Palomar Medical Inc. and MKS Instruments Inc. In 2004 Mr. Benzerrouk was involved in the founding of Energetiq technology Inc. a developer and a manufacturer of short wavelength light sources.

Reinhold Ludwig (SM) is on the faculty of the Electrical and Computer Engineering Department, with joint appointments in the Mechanical and Biomedical Engineering Departments, of Worcester Polytechnic Institute. After earning his MSEE at the University of Wuppertal, Germany, in 1983 he obtained his Ph.D. from Colorado State University, Ft. Collins, CO, in 1986, and joined WPI as an Assistant Professor. In 1990 he was promoted to Associate and in 1996 to full Professor. He spent industrial appointments at Hewlett Packard Corporation, United Technologies, and most recently at InsightMRI where he is also Chief Scientific Officer. Dr. Ludwig has published extensively on nondestructive evaluation and coil design in magnetic resonance imaging. He is author of the textbook RF Circuit Design: Theory and Applications by Prentice-Hall.

Report No. 06-# 2 APPENDIX B

On-Line Testing of Green-State P/M Compacts Through Active and Passive Thermography

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

1Powder Metallurgy Research Center METAL PROCESSING INSTITUTE

and 2Department of Electrical and Computer Engineering

Worcester Polytechnic Institute, Worcester, MA 01609

ABSTRACT

A complete on-line inspection system of P/M parts, particularly in their pre-sintered state, has always been a challenge that is difficult to achieve in an efficient way. Due to their fragile nature, green-state P/M compacts require a judicious testing approach that cannot involve direct contact of the samples either for energy deposition or imaging.

This paper discusses a novel approach that provides a full quality assessment of green-state compacts early in the manufacturing process. The method is based on an active thermography methodology whereby electric energy is deposited into the compact in a contact-less fashion through induction heating. Thermal data is then collected and analyzed in an effort to yield part integrity and process stability information. In this paper we will discuss our design approach and a proof-of-concept instrument with associated data processing software. Toward this end we will first review the underlying physical principles, followed by a brief discussion of the test arrangement, associated software development, and automated defect evaluation. As part of our experimental data processing, we will present results that are collected both in a laboratory setting and in an industrial manufacturing environment. The sample analyses are carried out through a custom-developed software package.

INTRODUCTION

In this paper we establish an IR-based nondestructive evaluation (NDE) methodology that ultimately will enable one hundred percent quality assessment early in the P/M manufacturing process. To achieve this goal we have designed and tested an apparatus capable of detecting surface and sub-surface defects in green-state P/M compacts. As reported elsewhere [1] the theoretical modeling approach is based on the concepts of heat flow, i.e. thermal energy that is generated through electromagnetic power deposition and temperature recording over the compact’s surface topology. Subsequent temperature data acquisition and processing by a digital computer enables us to gain valuable on-line information regarding part integrity as well as process stability. The theoretical modeling of the heat deposition and transport mechanisms can be used as a test bed to establish a baseline for our testing procedure. Due to the complex nature of the thermo-electric problem computational modeling techniques must be used [1, 2] to assess the limitations inherent associated with system sensitivity and acquisition speed to the images [1,2]; it allows us to critically validate the inspection approach. We tested complex parts exposed to induction heating in an effort to achieve high-resolution imaging and real time processing. Preliminary testing reveals that this newly developed pulsed thermography system can be employed to detect subsurface defects in green-state parts. Practical measurements agree well with theoretical predictions. The inspection approach presently under development targets the testing of all green-state compacts as they exit the compaction press at speeds of up to 1,000 parts per hour. TEST ARRANGEMENT Figure 1 depicts the dynamic IR testing arrangement where a function generator controls both the current injection and the camera recording of the sequentially acquired thermal images. The function generator is capable of providing either a programmable pulse or a step input voltage. Specifically, the leading pulse edge is used as a trigger to start data recording as well as controlling the power generator of an electromagnetic induction coil. This generator delivers power up to 10kW in burst mode and up to 5kW in continuous, or harmonic, mode. It is also capable of driving a variety of inductive loads such as a sample-specific excitation coil. In our inspection application the parts are suspended over the coil, and special care is taken in designing the coil layout. This includes a study of the magnetic field generated and the eddy current energy coupling into the compact. The usual approach of induction heating is to position the compact along the center axis of the coil winding where the magnetic flux density is at its maximum. However, in order to avoid obstructing the view of the camera system, we suspend the part above the coil plane to simulate the conveyor belt. This condition results in somewhat weaker field

penetration and a concentration of heating to the bottom of the part, whereas the topside is heated through thermal conduction. This non-uniform heat deposition can be remedied by custom designed coils, including “doughnut” shaped coils, where the turns are concentric and a magnetic core locate at the bottom forcing the magnetic field upwards. The resulting better electric energy coupling into the part enables uniform heating, a process that is highly desirable for the detection of subsurface defects.

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Figure 1: Block diagram of the complete IR test system for the inspection of green state

P/M compacts.

SOFTWARE DEVELOPMENT

In addition to the remote electromagnetic power deposition scheme, we have developed a custom software package that directly interfaces with the IR camera system. It is application-specific in the sense that the thermal data can be used to provide the user with feedback relative to the integrity of the samples under test. Furthermore, valuable information regarding process stability can be obtained by monitoring the speed of the compaction press. To extend the usability of the IR detection instrument to enable quality control, we have constructed two basic software modules:

A real-time IR imaging system with a simple and friendly graphical user interface (GUI) that can be used by the press operators and quality engineers (it is intended to be deployed in the manufacturing line with pass/ fail feedback).

A comprehensive data visualization and analysis system for a more in-depth failure

analysis. Functionally our software package offers a number of unique features; they include in particular

Full control of the camera system (on/off, zoom, focus, recording for local or remote storage) as well as functions common to computer vision systems,

Real time data collection and processing,

Image display (real time IR scene and processed image), and

Automatic defect detection.

ON-LINE TESTING TOPOLOGY The diagram depicted in Figure 2 details the steps taken to perform the on-line IR testing. Two major functions are completed here. First, the defect detection is conducted by comparing a sequence of images to a reference frame or image to permit efficient, automatic detection. Second, a simple speed measurement will provide the press operators with feedback on the compaction process stability. To maximize efficiency, the user can set the desired frame rate by either reducing the amount of data to be processed and stored, or by increasing the amount of data processing and storage for detailed analysis. The default setting for the test system is not to record data unless prompted by the user, or if a defect is flagged. Figure 3 shows the user interface that targets a detailed data analysis which enables the quality engineer to gain full access to the thermal data; it provides basic analysis tools including spot temperature recording, averaging, and alarms. In addition to this comprehensive GUI, the software package has a built-in interface for the press operators and technicians on the manufacturing floor. This interface is limited to alarms and basic display of thermographic images.

Figure 2: Overall software flow chart for the on-line IR testing of P/M compacts.

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Figure 3: A snap-shot of a computer screen as part of the data analysis GUI.

OFF-LINE TESTING TOPOLOGY: AUTOMATIC DEFECT DETECTION The off-line testing topology incorporates an automatic defect detection technique based on a “region-growing algorithm”. This method results not only in defect detection, but also in displaying two dimensional spatial characteristics of the defect. Although not included in this current setup, one can infer defect depth information from the contrast setting, as the two terms are inversely proportional.

The region-growing algorithm is summarized as follow [Error! Bookmark not defined.]:

• Compute the mean and standard deviation of the pixel intensities to reduce the amount of data processing.

• Detect the pixels with the highest contrasts (“hottest”) in every region: they constitute seeds.

• Start the defect shape extraction by growing a region around the seed. • Each seed is processed individually and assigned its own threshold.

• Neighbors are computed using a recursive procedure and assuming an eight connectivity (i.e. all pixels surrounding the seeds).

• Stop the region growing once the background pixels or border pixels are met.

This algorithm was implemented and complex gears with corner defects were tested. Figure 4 presents the results of our test; the software was able to detect the defect in real time.

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Figure 4: Automatic defect detection; the “+” points to the center of the flaw.

CONCLUSIONS

Our IR-based NDE test system addresses the need of P/M manufacturers in rapid defect detection in green-state compacts by providing real time feedback about part integrity as well as process stability with no intrusion or added process steps. Furthermore, testing in a real manufacturing setting shows that the method is versatile and is capable of handling different material compositions. Furthermore, it appears to be robust and immune to thermal “noise” from the plant surrounding. A fully P/M manufacturing-compliant prototype system was constructed and tested; it utilizes the heat residue in the compacts as they exit the compaction press. The prototype further includes a custom software package designed to meet the requirements of the P/M industry by tailoring the functionality and the feedback to the application. Testing conducted thus far indicate that the system is successful in detecting simulated defects.

1 cm

However, extensive testing under varying process conditions with realistic flaws and defects need to be performed before complete on-line defect detection is established. Moreover, process monitoring as related to part density variation can be explored.

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