Arc-Welding Spectroscopic Monitoring based on Feature Selection and Neural Networks

Sensors

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.