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Sensors 2015, 15(5), 10100-10117; doi:10.3390/s150510100

Unsupervised Classification of Surface Defects in Wire Rod Production Obtained by Eddy Current Sensors

1
Centro Tecnológico CARTIF, Parque Tecnológico de Boecillo 205, 47151 Boecillo, Valladolid, Spain
2
Instituto de las Tecnologías Avanzadas de la Producción, Universidad de Valladolid, Paseo del cauce 59, 47011 Valladolid, Spain
3
ISEND S.A., Parque Tecnológico de Boecillo, Luis Proust 10, 47151 Boecillo, Valladolid, Spain
*
Author to whom correspondence should be addressed.
Academic Editor: Vittorio M.N. Passaro
Received: 5 March 2015 / Revised: 20 April 2015 / Accepted: 22 April 2015 / Published: 29 April 2015
(This article belongs to the Section Physical Sensors)
View Full-Text   |   Download PDF [286 KB, uploaded 29 April 2015]   |  

Abstract

An unsupervised approach to classify surface defects in wire rod manufacturing is developed in this paper. The defects are extracted from an eddy current signal and classified using a clustering technique that uses the dynamic time warping distance as the dissimilarity measure. The new approach has been successfully tested using industrial data. It is shown that it outperforms other classification alternatives, such as the modified Fourier descriptors. View Full-Text
Keywords: dynamic time warping; cluster analysis; modified Fourier descriptors; unsupervised classification; wire rod manufacturing; eddy current inspection; nondestructive testing dynamic time warping; cluster analysis; modified Fourier descriptors; unsupervised classification; wire rod manufacturing; eddy current inspection; nondestructive testing
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Saludes-Rodil, S.; Baeyens, E.; Rodríguez-Juan, C.P. Unsupervised Classification of Surface Defects in Wire Rod Production Obtained by Eddy Current Sensors. Sensors 2015, 15, 10100-10117.

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