The thermographic signal reconstruction method: A powerful tool for the enhancement of transient thermographic images

Balageas, D.; Roche, Jean‐Michel; Leroy, François-Henri; Liu, Wei Min; Gorbach, Alexander M.

doi:10.1016/j.bbe.2014.07.002

Cited by 98 publications

(48 citation statements)

References 16 publications

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“…Other details about the testing parameters for the PPT technique can be found in references [17][18][19][20][21][22][23][24][25][26][27][28][29][30][31][32]. The Fast Fourier Transform (FFT) algorithm, available in software packages such as MatLab ® , greatly reduces the computation time and is therefore privileged.…”

Section: Post-processing Algorithms: Thermal Signal Reconstruction (Tsr)mentioning

confidence: 99%

“…The Pulsed Thermography (PT) technique has been applied on an aluminum specimen with flat bottom holes to simulate the presence of defects. Several algorithms have been implemented to elaborate raw thermal data: Pulsed Phase Thermography (PPT) [12][13][14][15][16][17], Thermal Signal Reconstruction (TSR) [18][19][20][21][22][23][24], Principal Component Thermography (PCT) [25][26][27][28][29][30], Slope and Correlation coefficient (R 2 ) [31,32].…”

Section: Introductionmentioning

confidence: 99%

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A Quantitative Comparison among Different Algorithms for Defects Detection on Aluminum with the Pulsed Thermography Technique

D’Accardi

Palumbo

Tamborrino

et al. 2018

Metals

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Pulsed thermography is commonly used as a non-destructive technique for evaluating defects within materials and components. In the last few years, many algorithms have been developed with the aim to detect defects and different methods have been used for detecting their size and depth. However, only few works in the literature reported a comparison among the different algorithms in terms of the number of detected defects, the time spent in testing and analysis, and the quantitative evaluation of size and depth. In this work, starting from a pulsed thermographic test carried out on an aluminum specimen with twenty flat bottom holes of known nominal size and depth, different algorithms have been used with the aim to obtain a comparison among them in terms of signal to background contrast (SBC) and number of detected defects by analyzing different time intervals. Moreover, the correlation between SBC and the aspect ratio of the defects has been investigated. The algorithms used have been: Pulsed Phase Thermography (PPT), Slope, Correlation Coefficient (R2), Thermal Signal Reconstruction (TSR) and Principal Component Thermography (PCT). The results showed the advantages, disadvantages, and sensitivity of the various thermographic algorithms.

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Section: Post-processing Algorithms: Thermal Signal Reconstruction (Tsr)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Quantitative Comparison among Different Algorithms for Defects Detection on Aluminum with the Pulsed Thermography Technique

D’Accardi

Palumbo

Tamborrino

et al. 2018

Metals

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“…Different from DAC, TSR models the surface temperature responses using low order polynomials. Due to the good performance in noise reduction and data compression, TSR becomes a commonly used method and has been regarded as a great breakthrough in the field of PT [13]. However, TSR cannot eliminate the effects of non-uniform backgrounds.…”

Section: Introductionmentioning

confidence: 98%

Improved non-destructive testing of carbon fiber reinforced polymer (CFRP) composites using pulsed thermograph

et al. 2015

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“…Drawback of this method is a large set of parametric images ai, even an extended TSR procedure [8] with the calculation of the 1 st and 2 nd derivative is unacceptable for medical personnel in clinical settings.…”

Section: Fig 5 A) Photograph Of the Burned Abdomen On Post Burn Daymentioning

confidence: 99%

TSR method for burns investigation approach

Kaczmarek¹

2018

Proceedings of the 2018 International Conference on Quantitative InfraRed Thermography

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The article presents the possibilities of applying the TSR method for the diagnosis of burn wounds. The wound area is stimulated by cold gas and a sequence of thermograms of heating the tissue is recorded. Next, TSR algorithms are used to determine the parameters that allow the wound to be classified into one of the classes: the wound heals within three weeks, the wound will not heal in three weeks. The method was validated on a series of in-vivo experiments on animals and on several clinical cases.

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The thermographic signal reconstruction method: A powerful tool for the enhancement of transient thermographic images

Cited by 98 publications

References 16 publications

A Quantitative Comparison among Different Algorithms for Defects Detection on Aluminum with the Pulsed Thermography Technique

A Quantitative Comparison among Different Algorithms for Defects Detection on Aluminum with the Pulsed Thermography Technique

Improved non-destructive testing of carbon fiber reinforced polymer (CFRP) composites using pulsed thermograph

TSR method for burns investigation approach

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