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Classification of defects in a thermal barrier coating layer using the fuzzy C-means algorithm

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Abstract

A thermally grown oxide (TGO) layer of Al2O3 is formed between a CoNiCrAlY bond coating and a zirconia top coating of a thermal barrier coating (TBC) system on an Inconel 738 substrate during exposure at 1050°C. Thick TGO is vulnerable to damage in terms of cracking and spallation. In order to estimate the TBC failure, fundamental damage data of TGO that is induced by compressed air are monitored to determine the failure mode and the state of damage by using a nondestructive acoustic emission (AE) system. The defects of the TGO are detected and evaluated by means of AE signal analysis with the root mean squared value in the frequency range of 100 kHz to 400 kHz. The thickness of the TGO increased with the oxidation time. The RMS (Root Mean Square) value decreased almost linearly as the TGO thickness increased up to the failure of the TBC. The amplitude of the AE signal decreased dramatically when the TGO was delaminated. The AE signals for pattern classification were evaluated in accordance with the TBC layer. It is conceivable that the center value represents the damage state of the TBC coating.

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Abbreviations

M:

Ni, Fe, Co or their combination

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Correspondence to Jeong-Suk Kim.

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Kim, PH., Kim, JS., Park, JH. et al. Classification of defects in a thermal barrier coating layer using the fuzzy C-means algorithm. Int. J. Precis. Eng. Manuf. 16, 53–57 (2015). https://doi.org/10.1007/s12541-015-0006-4

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  • DOI: https://doi.org/10.1007/s12541-015-0006-4

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