Reconstruction and enhancement of active thermographic image sequences

Shepard, Steven M.; Lhota, James R.; Rubadeux, Bruce A.; Wang, David; Ahmed, T.

doi:10.1117/1.1566969

Cited by 405 publications

(219 citation statements)

References 3 publications

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“…1for both the semi-infinite body as well as a finite thickness plate. It has been found that the plots of first and second derivatives of the ( ) with respect to ( ) are quite informative as demonstrated by Shepard et al [7]. These are referred to as first and second derivatives, or 1d and 2d by Shepard.…”

Section: Introductionmentioning

confidence: 70%

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Normalization and sound zone determination in pulse thermographic NDE

Sripragash¹,

Sundaresan²

2017

AIP Conference Proceedings

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Abstract. Thermographic nondestructive evaluation is quick and effective in detecting damage particularly for composite structures. Pulse thermographic nondestructive evaluation (TNDE) technique can potentially provide information on defect dimensions, such as the depth at which the defect is located. However, there are a number of extraneous variables that affect the signal obtained during these tests, such as non-uniformity in the heat pulse applied and differences in the emissivity of the surfaces from specimen to specimen. In addition, the identification of defect free areas in the image is a challenge. As in other NDE procedures calibration specimens would be of help, but calibration specimens corresponding to complex damage states in composite materials are difficult to fabricate. Results from validated numerical simulations can complement calibration specimens. However, the thermo-mechanical properties of the test object as well as the amount of heat energy absorbed in the field tests are not readily available for such models. This paper presents an extension of the thermographic signal reconstruction (TSR) procedure in which the temperature and the time scales are respectively normalized with equilibrium temperature and the break time. A benefit of such normalization is the ability to directly measure the defect depth as a fraction of plate thickness. In order to implement this normalization procedure, sound zone profile definition is required. A new approach for determining sound zone profile has been developed. Finally, determination of sound zone is affected by non-uniform heating, and a method of minimizing the effects of non-uniform heating is proposed. The performance of these new approaches on actual experimental results are presented.

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Section: Introductionmentioning

confidence: 70%

“…al. [7] is very effective. Non uniformity is a problem when it comes to extracting the temperature data and finding the sound zones.…”

Section: Introductionmentioning

confidence: 99%

Normalization and sound zone determination in pulse thermographic NDE

Sripragash¹,

Sundaresan²

2017

AIP Conference Proceedings

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“…In image-based technique contrast images are used for defect characterization, and in pixel-based technique the thermographic profile of selected pixels is analysed. In quantitative analysis of flash thermography, as proposed by Shepard et al in their Thermographic Signal Reconstruction (TSR) technique [4] time derivatives of the thermal profile in logarithmic domain of pixels also found to be useful.…”

Section: Introductionmentioning

confidence: 99%

Use of Numerical Model and Nonlinear Regression in Determining Thermo-Material Properties of Thermal Barrier Coatings Using Flash Thermography

Sripragash¹,

Goldammer²,

Koerdel³

2018

Proceedings of the 2018 International Conference on Quantitative InfraRed Thermography

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Determination of thermo-material properties of Thermal Barrier Coatings (TBC) is critical in gas turbine industry. In this study, with the aid of a numerical model and non-linear regression, material properties of the TBC were determined [1], [2]. The effect of thicknesses of second and third layers on the thermographic responses were also analysed. A precalculated grid concept was used for the estimation of material properties. A significant increase in computational speed was observed when pre-calculated grid data was used for regression analysis.

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“…Combining these two techniques also would be beneficial [3]. Thermographic Signal Reconstruction (TSR) introduced by Shepard etl al [4] is found to be one of the best pixel based techniques for quantitative defect characterization. The TSR second derivative (2d) plots can be used to estimate the depth of defects.…”

Section: Introductionmentioning

confidence: 99%

A normalization procedure and determination of axisymmetric defect characters of composite panels

Ingle¹,

Sripragash²,

Sundaresan³

2017

AIP Conference Proceedings

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Abstract. In Pulse Thermographic Nondestructive Evaluation (TNDE), the thermographic signals are heavily influenced by material directionalities, therefore comparison of thermographic results are challenging. In this study a normalization procedure is introduced which simplifies the analysis and requires only break time, equilibrium temperature, and diffusivity ratios of transverse to lateral diffusivity. The normalization for the composite panels was proved to be effective for quasiisotropic carbon epoxy composite panels used in the study. A correlation method was utilized to estimate the defect diameter and depth of a composite panel. The correlation method utilizes several numerical models to estimate the correct defect parameter of the experimental specimen. Thermographic Signal Reconstruction (TSR) second derivatives found to be effective in differentiating the defect parameters.

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Reconstruction and enhancement of active thermographic image sequences

Cited by 405 publications

References 3 publications

Normalization and sound zone determination in pulse thermographic NDE

Normalization and sound zone determination in pulse thermographic NDE

Use of Numerical Model and Nonlinear Regression in Determining Thermo-Material Properties of Thermal Barrier Coatings Using Flash Thermography

A normalization procedure and determination of axisymmetric defect characters of composite panels

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