Infrared Testing of CFRP

Components: Comparisons of

Approaches using the Tanimoto

Criterion

by

Xavier Maldague

Saeed Sojasi, Fariba Khodayar,

Fernando Lopez, Clemente

Ibarra-Castando, Xavier

Maldague, Vladimir P. Vavilov,

Arseny O. Chulkov

Xavier.Maldague@gel.ulaval.ca

http://mivim.gel.ulaval.ca

ND

T in C

anada 2015 Conference, June 15-17, 2015, E

dmonton, A

B (C

anada) - ww

w.ndt.net/app.N

DT

Canada2015

2

Outline

1. Review;

2. Case study;

3. Conclusions.

1. Review1. Review

3

4

Active and passive thermography scenarios

Pulsed thermography

5

Lock-in thermography

6

Vibro-thermography

7

LED

8

In this paper, high power LED arrays for pulse and lock-in

thermography are studied. Long pulse LED is compared to

conventional flash thermographic and square wave lock-in LED

excitation is compared to conventional lock-in approach. The

results with LEDs in fact are not good.

Burst vibro-thermography (left) and lock-in vibro-

thermography (right)

9

10

Transient regime

T

t

I

t

Pulsed thermography

defective

non-defective

Stationary regime

A

t

ωI

t

Lock-in thermography

φSa

φdef

PT vs. LT: Setup

milliseconds

11

PT vs. LT: Data acquisition

Pulsed thermography Lock-in thermography

tN

x

y

. . .t1 t2 t3t

∆t

S(t)

s

I

s1

s2s3

s4

ω t

t

tN

x

y

. . .t1 t2 t3t

∆t

TSa(t)

Td(t)

T

t. . .t1 t2 t3 tN

∆t

TSa(t)

tNtw ∆⋅=)(

Td(t)

( ) ( )242

231 SSSSA −+−=

−

−=

42

31arctanSS

SSφ

12

PT vs. LT: Basic processing

Pulsed thermography Lock-in thermography

tN

x

y

. . .t1 t2 t3t

∆t

defect

TSa(t)

Td(t)

T

t. . .t1 t2 t3 tN

∆T

0

∆Tmax

)()()( tTtTtTaSd −=∆

fN

x

y

. . .f1 f2 f3f

∆f

defect

φSa(t)

φd(t)

0

φi,j(f)

. . .

f

f1 f2

∆f

φSa(f)

φd(f)

f3

∆φi,j(f)

−

−=

42

31arctan1 SS

SSωφ

fN

Advanced processing

�Differential absolute contrast, DAC

� Thermographic signal reconstruction, TSR

�Pulsed phase thermography, PPT

13

( )tTt

ttTT ddac

′⋅′

−=∆ )(

( ) ( )te

QT πln

2

1lnln −

=∆

( ) nn

N

k

Nnkjn tkTtF ImReexp

1

0

)2( +=∆∆= ∑−

=

− π

Advanced processing

�Principal components thermography, PCT

�Partial least square, PLST

14

TUSVA =

FUQY

ETPX

T

T

+=

+=

PT characteristics LT characteristics VT characteristics

PT, LT and VT characteristics

� Several frequencies tested at a time (fast);

� Transient regime;

� Requires synchronization between the heat pulse and the acquisition;

� Affected by typical active thermography problems (non-uniform heating, emissivity variations, reflections, surface geometry..);

� Quantification requires advanced processing techniques;

� Typically, lots of energy are used in a single experiment

� One frequency tested at a time;

� Steady state regime;

� Requires monitoring the time dependence between the reference input signal and the output signal;

� Phase data is less affected than the raw temperature by typical active thermography problems;

� Quantification is straightforward through the diffusion length equation;

� Better control on the energy delivered to the specimen

� Under the effect of mechanical vibrations induced externally to the structure at a few fixed frequencies

� Heat is related by friction precisely at defect locations

� Makes use of mechanical waves to directly stimulate defects without heating the surface as in optical methods

� Mechanical elastic waves travel faster in solids and liquids than through the air

3. Case study:

CFRP006

3. Case study:

CFRP006

16

Setup

17

MWIR cooled

camera

MWIR cooled

camera

2 halogen lamps

Carbon fiber–

reinforced polymer

Carbon fiber–

reinforced polymer

Schematic representation and defect location for

specimen CFRP006

18

Summary of quantification results of PT

19

Raw image TSR(polynomial 4 and derivative 1) PCT

PPT PLST

Summary of quantification results of PT

20

0

10

20

30

40

50

60

70

80

90

100

t =1 .109 s polynomial 4 and

derivative 1 t = 0.03 6 s

polynomial 4 and

derivative 2 t = 0.05 4 s

EOF4 Phase image, f = 0.27

Hz

4th PLS loading

Pulsed Thermography

DAC

TSR

PCT

PPT

PLS

Summary of quantification results of LT(f=100mHZ)

21

Raw image

PCT

PPT

PLST

22

0

10

20

30

40

50

60

70

80

90

100

f = 100 mHz f = 200 mHz f = 300 mHz f = 400 mHz f = 700 mHz f = 1200 mHz

Lock-in Thermography

PCT

PPT

PLS

Summary of quantification results of LT

Summary of quantification results of VT(20kHz 0.125Hz 00-50 pct)

23

Raw image

PCT

PPT

PLST

VT(20kHz 0.125Hz 00-50 pct)

24

0

10

20

30

40

50

60

70

20kHz 0.125Hz 00-50 pct 20kHz 0.250Hz 00-50 pct 20kHz 0.250Hz 20-50 pct 20kHz 0.500Hz 20-50 pct 20kHz 0.500Hz 30-50 pct

Vibrothermography

PCT

PPT

PLS

Summary of quantification results of LED

25

0

5

10

15

20

25

30

35

40

45

50

t = 0.98 s polynomial 4 and

derivative 1

polynomial 4 and

derivative 2

EOF3 EOF2 f = 0.25 Hz f = 0.30 Hz 2nd PLS loading 2nd PLS loading

Tan

imo

to c

rite

rio

n

%

Achsentitel

LED

DAC (Pulsed thermography) TSR (Pulsed thermography) PCT (Pulsed thermography) PCT (Lock-in)

PPT (Pulsed thermography ) PPT (Lock-in) PLS (Pulsed thermography) PLS (Lock-in)

4. Conclusions4. Conclusions

26

Conclusion

27

It has been confirmed experimentally that infrared thermography is

a useful tool in non-destructive testing of CFRP composite. There

are different thermal NDT techniques of which efficiency depends

on material characteristics test conditions. In this paper, four types

of stimulating sources (pulse, lock-in, vibro and LED) have been

applied to a CFRP laminate. The qualitative defect detection based

on Tanimoto criterion was used to compare different signal

processing methods. In the raw images, the defects which are large

and near the surface are easily observed. To detect the defects

which are smaller and deeper, signal processing techniques such as

TSR, DAC, PPT, PCT and PLST need to be used. Surprisingly, the

results of using LED heating have not confirmed efficiency of this

stimulation approach, probably, because of slow and low power

input.

28