Quantification of defects in composites and rubber materials using active thermography

Lahiri, B.B.; Bagavathiappan, S.; Reshmi, P. R.; Philip, John; Jayakumar, T.; Raj, Baldev

doi:10.1016/j.infrared.2012.01.001

Cited by 65 publications

(25 citation statements)

References 32 publications

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“…DITI has been used in many areas of medical science as well as in the field of non-destructive testing (NDT). In the field of NDT, it is mainly used for surface defect detection and online monitoring of processes [2][3][4].…”

Section: Introductionmentioning

confidence: 99%

Automatic Intelligent Asymmetry Detection Using Digital Infrared Imaging with K-Means Clustering

Kim

Song

2015

Int. J. Fuzzy Log. Intell. Syst.

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Digital infrared thermal imaging is a non-invasive adjunctive diagnostic technique that allows an examiner to visualize and quantify changes in skin surface temperature. The asymmetry of temperature differences between the diseased and the contralateral healthy body parts can be automatically analyzed and has been studied in many areas of medical science. In this paper, we propose a method for intelligent automatic asymmetry detection based on a K-means analysis and a YCbCr color model. The implemented software successfully visualizes an asymmetric distribution of colors with respect to the patients' health status.

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Section: Introductionmentioning

confidence: 99%

Automatic Intelligent Asymmetry Detection Using Digital Infrared Imaging with K-Means Clustering

Kim

Song

2015

Int. J. Fuzzy Log. Intell. Syst.

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“…Comparing Eqs. 8 and 10, the discriminating factor could be tracked down on the C 1 term that we assume here to be the same, but that it should be linked to the nature of the material analyzed [68,69]. Therefore, the C 1 term fits very well in the aluminum case.…”

Section: Methods Of Analysis Of the Irt Datamentioning

confidence: 93%

Ceramics and defects

Сфарра

Perilli

Paoletti

et al. 2015

J Therm Anal Calorim

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The feasibility of square-pulsed thermography nondestructive testing for the detection of defects in one ceramic material sample has been carried out by finite element (FE) analysis. In particular, a ceramic plate containing defects of different diameters, depths, locations, nature, and shapes has been numerically investigated by means of Comsol Ò Multiphysics computer program, taking into account the results coming from both a MATLAB TM script and the infrared thermography (IRT) technique. Indeed, the FE method simulates through a 3D model the heat transfer process induced into the ceramic material by two halogen lamps that have been applied in order to provoke an optimum thermal stress. Moreover, further defects like cracks arose beneath the surface of the plate due to the shrinkage process, have been discovered, and contrasted using a non-usual segmentation algorithm that when correlated in the time to IRT data simulates the thermo-elastic effect. Following the non-direct procedure proposed, both the depth of each defect and its main dimensions have been retrieved into a satisfactory accuracy.

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“…The necessary conditions for IRNDT testing method are homogeneous thermal excitation of whole inspected surface, limited inspection depth combined with defects size and elimination of reflections from surrounding and/or thermal excitation source directly to the detector of IR camera. According to the application, a suitable combination of excitation method, analysis method and evaluation method including their parameters has to be found [4][5][6][7].…”

Section: Introductionmentioning

confidence: 99%

Application of IRNDT method for materials in wide range of thermal diffusivity

Veselý¹,

Švantner²

2016

Proceedings of the 2016 International Conference on Quantitative InfraRed Thermography

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Infrared non-destructive testing method (IRNDT) is suitable supplement to classic non-destructive testing methods (NDT). The advantage of IRNDT method is fast and non-contact measurement and evaluation that is available to various industrial and research applications. The method is suitable for both production process inspection (material inhomogeneities, inner structure of multilayer parts, cracks, ...) and subsequent component inspection during service (cracks, layers delamination, etc.) The possibility of defects detection is influenced by IRNDT method parameters, geometric orientation of defects and by physical properties of material. The influence of material thermal properties on the detectability of defects is discussed.

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Quantification of defects in composites and rubber materials using active thermography

Cited by 65 publications

References 32 publications

Automatic Intelligent Asymmetry Detection Using Digital Infrared Imaging with K-Means Clustering

Automatic Intelligent Asymmetry Detection Using Digital Infrared Imaging with K-Means Clustering

Ceramics and defects

Application of IRNDT method for materials in wide range of thermal diffusivity

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