Unsupervised classification of surface defects in wire rod production obtained by eddy current sensors.
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.
Centro Tecnológico CARTIF, Parque Tecnológico de Boecillo 205, 47151 Boecillo, Valladolid, Spain. sersal@cartif.es.
Sergio
S
Saludes-Rodil
Instituto de las Tecnologías Avanzadas de la Producción, Universidad de Valladolid, Paseo del cauce 59, 47011 Valladolid, Spain. enrbae@eis.uva.es.
Enrique
E
Baeyens
ISEND S.A., Parque Tecnológico de Boecillo, Luis Proust 10, 47151 Boecillo, Valladolid, Spain. carlos@isend.es.
Carlos P
CP
Rodríguez-Juan