Automatic defect detection and characterization by thermographic images based on damage classifiers evaluation

• Autorzy: Dinardo Giuseppe , Fabbiano Laura , Tamborrino Rosanna , Vacca Gaetano

Identyfikatory

DOI

10.24425/mms.2020.132771

• Języki publikacji: EN

Abstrakty

EN

In the framework of non-destructive evaluation (NDE), an accurate and precise characterization of defects is fundamental. This paper proposes a novel method for characterization of partial detachment of thermal barrier coatings from metallic surfaces, using the long pulsed thermography (LPT). There exist many applications, in which the LPT technique provides clear and intelligible thermograms. The introduced method comprises a series of post-processing operations of the thermal images. The purpose is to improve the linear fit of the cooling stage of the surface under investigation in the logarithmic scale. To this end, additional fit parameters are introduced. Such parameters, defined as damage classifiers, are represented as image maps, allowing for a straightforward localization of the defects. The defect size information provided by each classifier is, then, obtained by means of an automatic segmentation of the images. The main advantages of the proposed technique are the automaticity (due to the image segmentation procedures) and relatively limited uncertainties in the estimation of the defect size.

Słowa kluczowe

EN

thermography; non-destructive testing; thermal barrier coatings; image segmentation; uncertainty analysis

• Wydawca: Komitet Metrologii i Aparatury Naukowej PAN
• Czasopismo: Metrology and Measurement Systems
• Rocznik: 2020
• Tom: Vol. 27, nr 2
• Strony: 219--242
• Opis fizyczny: Bibliogr. 31 poz., fot., rys., tab., wykr.

Twórcy

autor

Dinardo Giuseppe

• Politecnico di Bari University, Department of Mechanics, Mathematics and Management, Via E. Orabona 4, 70125 Bari, Italy

autor

Fabbiano Laura

• Politecnico di Bari University, Department of Mechanics, Mathematics and Management, Via E. Orabona 4, 70125 Bari, Italy

autor

Tamborrino Rosanna

• Politecnico di Bari University, Department of Mechanics, Mathematics and Management, Via E. Orabona 4, 70125 Bari, Italy

autor

Vacca Gaetano

• Politecnico di Bari University, Department of Mechanics, Mathematics and Management, Via E. Orabona 4, 70125 Bari, Italy

Bibliografia

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Uwagi

PL

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).