@article{10902/841,
year = {2008},
month = {10},
url = {http://hdl.handle.net/10902/841},
abstract = {A new spectral processing technique designed for application in the on-line
detection and classification of arc-welding defects is presented in this paper. A noninvasive
fiber sensor embedded within a TIG torch collects the plasma radiation originated
during the welding process. The spectral information is then processed in two consecutive
stages. A compression algorithm is first applied to the data, allowing real-time analysis.
The selected spectral bands are then used to feed a classification algorithm, which will be
demonstrated to provide an efficient weld defect detection and classification. The results
obtained with the proposed technique are compared to a similar processing scheme
presented in previous works, giving rise to an improvement in the performance of the
monitoring system.},
publisher = {MDPI},
publisher = {Sensors, 2008, 8(10), 6496-6506},
title = {Arc-welding spectroscopic monitoring based on feature selection and neural networks},
author = {García Allende, Pilar Beatriz and Mirapeix Serrano, Jesús María and Conde Portilla, Olga María and Cobo García, Adolfo and López Higuera, José Miguel},
}