2026-04-30T00:42:41Zhttps://uvadoc.uva.es/oai/requestoai:uvadoc.uva.es:10324/578232022-12-19T20:00:38Zcom_10324_966com_10324_952com_10324_894col_10324_967
Unsupervised classification of surface defects in wire rod production obtained by Eddy current sensors
Saludes Rodil, Sergio
Baeyens Lázaro, Enrique
Rodríguez Juan, Carlos
Producción Científica
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.
2022-12-19
2022-12-19
2015
info:eu-repo/semantics/article
Sensors, 2015, vol. 18, n. 5, p. 10100-10117
1424-8220
https://uvadoc.uva.es/handle/10324/57823
10.3390/s150510100
10100
5
10117
Sensors
15
1424-8220
eng
https://www.mdpi.com/1424-8220/15/5/10100
info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by/4.0/
© 2015 The Author(s)
Atribución 4.0 Internacional
MDPI