&lt;title&gt;Enhancement and reconstruction of thermographic NDT data&lt;/title&gt;

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

doi:10.1117/12.459603

Cited by 60 publications

(35 citation statements)

References 2 publications

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“…Hence, different types of thermographic image analysis methods have been proposed for signal enhancement, e.g. thermographic signal reconstruction (TSR) [19,20], differential absolute contrast (DAC) [21,22], pulsed phase thermography (PPT) [23,24], principal component thermography (PCT) [25], etc., where TSR is frequently used for its performance in data compressing and noise reduction. Based on the Fourier diffusion equation, TSR applies polynomial filters to eliminate the noise contained in thermographic data.…”

Section: Introductionmentioning

confidence: 99%

Defect detection in CFRP structures using pulsed thermographic data enhanced by penalized least squares methods

Zheng

Chang

Yao

2015

Composites Part B: Engineering

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Section: Introductionmentioning

confidence: 99%

Defect detection in CFRP structures using pulsed thermographic data enhanced by penalized least squares methods

Zheng

Chang

Yao

2015

Composites Part B: Engineering

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“…TSR is popular and an attractive processing method spe− cially conceived to be used in PT data [2,3]. This technique brings important improvements and advantages over PT raw data, the most significant being the simplicity and accu− racy of quantitative measurement, increase of temporal and spatial resolution, reduction of high frequency noise and ability to produce time derivative images without generating additional noise.…”

Section: Thermographic Signal Reconstructionmentioning

confidence: 99%

Enhanced image processing for infrared non-destructive testing

López

Maldague

Ibarra-Castanedo

2014

Opto-Electronics Review

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This paper presents a review and in-depth analysis of three of the most popular techniques for processing PT images: differential absolute contrast, thermographic signal reconstruction and pulsed phase thermography. The fundamental concepts of the three techniques are reviewed and their application on thermal data obtained from the PT inspection on a carbon fibre reinforced specimen is analysed. Furthermore, a new promissory technique based on multivariate statistical analysis is also introduced and evaluated. The performance of the techniques is evaluated in terms of the signal-to-noise ratio at maximum signal contrast.

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“…Generally, a polynomial fitting in the Ln-Ln space is more appropriate when defects or hidden structures exists. [22]. Figure 11 gives an example of this procedure showing temperature plots fitted using a 4 th order function.…”

Section: Enhanced Thermographic Data Reduction Proceduresmentioning

confidence: 99%

IR Thermography applied to historical buildings

Grinzato¹

2002

Proceedings of the 2002 International Conference on Quantitative InfraRed Thermography

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Different kinds of discontinuities affecting historical building structures are detectable by thermal analysis of the surface temperature when submitted to suitable boundary conditions. The use of a quantitative approach is illustrated according to particular requirements of works of art. Principal sources of errors and failures in the interpretation of thermographic data are considered.Applications to massive masonry buildings are reported to illustrate recent results applying advanced processing algorithms to frescoes.

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<title>Enhancement and reconstruction of thermographic NDT data</title>

Cited by 60 publications

References 2 publications

Defect detection in CFRP structures using pulsed thermographic data enhanced by penalized least squares methods

Defect detection in CFRP structures using pulsed thermographic data enhanced by penalized least squares methods

Enhanced image processing for infrared non-destructive testing

IR Thermography applied to historical buildings

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