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• W2048587411 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." @default.
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• W2048587411 date "2008-10-21" @default.
• W2048587411 modified "2023-10-17" @default.
• W2048587411 title "Arc-Welding Spectroscopic Monitoring based on Feature Selection and Neural Networks" @default.
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• W2048587411 doi "https://doi.org/10.3390/s8106496" @default.
• W2048587411 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/3707464" @default.
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