Sensors | |
Arc-Welding Spectroscopic Monitoring based on Feature Selection and Neural Networks | |
P. Beatriz Garcia-Allende1  Jesus Mirapeix2  Olga M. Conde2  Adolfo Cobo2  | |
[1] Photonics Engineering Group, University of Cantabria, Avda. de los Castros S/N, 39005 Santander, Spain; | |
关键词: Arc-welding; fiber sensor; spectral processing; plasma spectroscopy; on-line monitoring; | |
DOI : 10.3390/s8106496 | |
来源: mdpi | |
【 摘 要 】
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 non-invasive 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.
【 授权许可】
CC BY
© 2008 by the authors; license Molecular Diversity Preservation International, Basel, Switzerland.
【 预 览 】
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RO202003190058196ZK.pdf | 1222KB | download |