Abstract
The methods of cluster analysis are applied to ultrasonic testing data of welded joints. The methods of principal component analysis, K-means clustering, and support vector machines are considered. The application methodology and the results obtained are presented.
Similar content being viewed by others
References
N. Cristianini and J. Shawe-Taylor, An Introduction to Support Vector Machines and Other Kernel-Based Learning Methods (Cambridge Univ. Press, Cambridge, 2000).
D. Meyer, “Support Vector Machines. The Interface to LIBSVM in Package e1071,” R News 1/3, 23–26 (2001).
N. P. Aleshin, V. E. Belyi, A. Kh. Vopilkin, A. K. Voshchanov, I. N. Ermolov, and A. K. Gurvich, Ultrasonic Techniques for Metal Materials Testing, Ed. by N. P. Aleshin (Mashinostroenie, Moscow, 1989) [in Russian].
Author information
Authors and Affiliations
Additional information
The article was translated by the authors.
Rights and permissions
About this article
Cite this article
Skomorokhov, A.O., Belousov, P.A. & Nakhabov, A.V. Cluster analysis of ultrasonic testing data. Pattern Recognit. Image Anal. 16, 82–84 (2006). https://doi.org/10.1134/S1054661806010263
Received:
Issue Date:
DOI: https://doi.org/10.1134/S1054661806010263