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dc.contributor.authorRiba Ruiz, Jordi-Roger
dc.contributor.authorCanals Parelló, Trini
dc.contributor.authorCantero Gómez, María Rosa
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria Elèctrica
dc.identifier.citationRiba, J.; Canals, T.; Cantero, M.R. Comparative Study of Multivariate Methods to Identify Paper Finishes Using Infrared Spectroscopy. "IEEE transactions on instrumentation and measurement", 09 Març 2012, vol. 61, núm. 4, p. 1029-1036.
dc.description.abstractRecycled paper is extensively used worldwide. In the last decades its market has expanded considerably. The increasing use of recycled paper in papermaking has led to the production of paper containing several types of impurities. Consequently, wastepaper mills are forced to implement quality control schemes for evaluating the incoming wastepaper stock, thus guarantying the specifications of the final product. The main objective of this work is to present a fast and reliable system for identifying different paper types. Therefore, undesirable paper types can be refused, improving the performance of the paper machine and the final quality of the paper manufactured. For this purpose two fast techniques, i.e., Fourier transform mid-infrared (FTIR) and reflectance near-infrared (*IR) were applied to acquire the infrared spectra of the paper samples. *ext, four processing multivariate methods, i.e., principal component analysis (PCA), canonical variate analysis (CVA), extended canonical variate analysis (ECVA) and support vector machines (SVM) were employed in the feature extraction –or dimension reduction– stage. Afterwards, the k nearest neighbors algorithm (k**) was used in the classification phase. Experimental results show the usefulness of the proposed methodology and the potential of both FTIR and *IR spectroscopic methods. Using the FTIR spectrum in association with SVM and k** the system achieved maximum classification accuracy of 100%, whereas using the *IR spectrum in association with ECVA or SVM and k** the system achieved maximum classification accuracy of 96.4%
dc.format.extent8 p.
dc.subjectÀrees temàtiques de la UPC::Enginyeria paperera
dc.subjectÀrees temàtiques de la UPC::Enginyeria química
dc.subject.lcshInfrared spectroscopy
dc.subject.lcshPaper finishing
dc.subject.lcshProcess control
dc.subject.lcshQuality Improvement
dc.titleComparative Study of Multivariate Methods to Identify Paper Finishes Using Infrared Spectroscopy
dc.subject.lemacEspectroscòpia infraroja
dc.subject.lemacPaper -- Acabat
dc.contributor.groupUniversitat Politècnica de Catalunya. MCIA - Motion Control and Industrial Applications Research Group
dc.contributor.groupUniversitat Politècnica de Catalunya. GIR - GIR Ambiental
dc.rights.accessOpen Access
dc.description.versionPostprint (published version)
local.citation.authorRiba, J.; Canals, T.; Cantero, M.R.
local.citation.publicationNameIEEE transactions on instrumentation and measurement

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