Abstract
Pulse or flash thermography is a method of nondestructive evaluation that finds subsurface flaws in materials by observing a heat pulse and subsequent cooldown using a thermal camera. A fundamental constraint of pulse thermography is lateral heat diffusion that tends to blur the shapes of defects. It can be difficult to interpret the thermal image sequence from a pulse thermography test. This paper presents a model-based inversion for pulse thermography that uses the known physics of heat conduction to as a basis for representing the recorded thermal image sequence. The technique provides a means to solve for the reflectivity distribution of defects across multiple layers, such as delaminations in a composite material. The layer reflectivity distributions provide a compact and concrete representation of the thermal image sequence. The technique gives excellent interpretability and resolution with minimal noise gain. Model-based inversion is demonstrated on several carbon fiber reinforced plastic (CFRP) specimens.
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Notes
Twice because half of the injected heat flows up and half flows down.
The first few rows of x correspond to the excitation pulse on the surface, for which the depth is zero, but scaling by zero would be obviously problematic. Some sort of scaling is necessary in order to be dimensionally compatible. Because there is plenty of data to evaluate the excitation source intensity the noise level is very low and a wide range of scaling factors would be adequate. In these tests we used an effective depth value corresponding to the time t3 of the 3rd usable frame, \(z=\sqrt {\pi \alpha _{z}t_{3}}\) and scaled the column by an additional factor of 50.
Do not confuse the spatial dimension x with the reflector amplitudes being solved for x
References
Maldague X (2001) Theory and practice of infrared technology for nondestructive testing. Wiley, New York
Ringermacher HI, Howard DR (2001) Synthetic thermal time-of-flight (STTOF) depth image. In: Proc review of progess in quantitative nondestructive evaluation, AIP Conf, Proc 557, 487. https://doi.org/10.1063/1.1373798
Shepard SM, Hou Y, Ahmed T, Lhota JR (2006) Reference-free interpretation of flash thermography data. BINDT Insight 48(5):298–301
Shepard SM, Lhota JR, Rebadeux BA, Wang D, Ahmed T (2003) Reconstruction and enhancement of active thermographic image sequences. Opt Eng 42(5):1337–1342
Shepard SM, Hou J, Lhota JR, Golden JM (2007) Automated processing of thermographic derivatives for quality assurance. Opt Eng 46(5):051008
Ringermacher HI (2013) Method of evaluating thermal diffusivity near lossy boundaries as an alternative to the Parker method. J Appl Phys 113:154903
Shepard SM, Hou Y, Ahmed T, Lhota JR (2006) Reference-free interpretation of flash thermography data. BINDT Insight 48(5):298–301
Vavilov V, Maldague X, Picard J, Thomas RL, Favro LD (1992) Dynamic thermal tomography, new NDE technique to reconstruct inner solids structure using multiple IR image processing. Review of Progress in Quantitative Nondestructive Evaluation 11
Vavilov V (2015) Dynamic thermal tomography: recent improvements and applications. NDT&E Intl 71:23–32
Lugin S, Netzelmann U (2007) A defect shape reconstruction algorithm for pulsed thermography. NDT&E Intl 40:220–228
Almond D, Lau SK (1994) Defect sizing by transient thermography, I. An analytical treatment. J Phys D: Appl Phys 27:1063
Saintey MB, Almond D (1995) Defect sizing by transient thermography. II. a numerical treatment. J Phys D: Appl Phys 28:2539
Plotnikov YA, Winfree WP (1998) Advanced image processing for defect visualization in infrared thermography. In: Proc SPIE 3361 Thermosense XX
Holland SD, Gregory E, Schiefelbein B (2016) Model-Based Inversion of flash thermography nondestructive evaluation measurements of composites. In: Proc Amer Soc composites
Holland SD Greensinversion model based inversion software, https://thermal.cnde.iastate.edu/greensinversion.xml
Beck JV, Cole KD, Haji-Sheikh A, Litkouhi B (1992) Heat Conduction Using Green’s Functions. Hemisphere Publishing
Bradski G (2000) The openCV Library, Dr. Dobb’s Journal of Software Tools 25(11):120–123
Tikhonov AN, Arsenin VY (1977) Solutions of ill posed problems. Wiley, New York
Ptaszek G, Cawley P, Almond D, Pickering S (2012) Artificial disbonds for calibration of transient thermography inspection of thermal barrier coating systems. NDT&E Int 45(1):71–78
Holland SD, Reusser RS (2016) Material evaluation by infrared thermography. Annu Rev Mater Res 46:287–303
Shepard SM, Lhota JR, Ahmed T (2009) Measurement limits in flash thermography. In: Proc SPIE 7299 Thermosense XXXI 72990T-1–7
Golub GH, Hansen PC, O’Leary DP (1999) Tikhonov regularization and total least squares. SIAM J Matrix Anal Appl 21(1):185–194
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This research was funded by NASA Early Stage Innovation under award NNX15AD75G.
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Holland, S., Schiefelbein, B. Model-based Inversion for Pulse Thermography. Exp Mech 59, 413–426 (2019). https://doi.org/10.1007/s11340-018-00463-2
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DOI: https://doi.org/10.1007/s11340-018-00463-2