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2022 №02 (02) DOI of Article
2022 №02 (04)

Technical Diagnostics and Non-Destructive Testing 2022 #02
Technical Diagnostics and Non-Destructive Testing #2, 2022, pp. 20-23

Automation of thermal non-destructive testing process by applying the method of complexing thermographs

D.V. Storozhik, A.G. Protasov, O.V. Muraviov, V.F. Petrik, D.V. Petrenko

National Technical University of Ukraine «Igor Sikorsky Kyiv Polytechnic Institute». 37 Peremohy Ave., 03056, Kyiv, Ukraine. E-mail: a.g.protasov@gmail.com

Experimental studies were conducted to improve the quality of thermograms obtained by thermal non-destructive testing. The method of image complexation based on wavelet transform using neural networks is applied. To determine the shape of the defect, a neural network was used, the architecture of which had layers that implement the convolution operation. Preliminary training of the neural network was implemented on the basis of a large number of thermal images of test objects that imitate various defects. The use of complex thermograms as input data for the neural network has signifi cantly reduced the error in determining the class of the defect in the image. The developed computer program for thermogram processing allows automating the process of thermal testing and increasing the probability of correctly determining the presence and form of the defect in the tested object. Ref. 9, Fig. 5.
Keywords: thermal non-destructive testing, image complexation, neural networks



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