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dc.contributor.author | Vitale, Raffaele | es_ES |
dc.contributor.author | Noord, Onno E. de | es_ES |
dc.contributor.author | Ferrer Riquelme, Alberto José | es_ES |
dc.date.accessioned | 2016-05-30T08:18:53Z | |
dc.date.available | 2016-05-30T08:18:53Z | |
dc.date.issued | 2015-12-15 | |
dc.identifier.issn | 0169-7439 | |
dc.identifier.uri | http://hdl.handle.net/10251/64903 | |
dc.description.abstract | [EN] This article explores the potential of kernel-based methods for fault diagnosis in batch process monitoring by combining Kernel-Principal Component Analysis and three common techniques which permit analyzing batch data by means of bilinear models: variable-wise unfolding, batch-wise unfolding and landmark feature extraction. Gower's idea of pseudo-sample projection is exploited to develop novel tools, the pseudo-sample based contribution plots, for diagnostic purposes. The results show that, when the datasets under study are affected by severe non-linearities, the proposed approach performs better than classical ones. | es_ES |
dc.description.sponsorship | This research work was partially supported by the Spanish Ministry of Economy and Competitiveness under the project DPI2011-28112-C04-02 and Shell Global Solutions International B.V. (Amsterdam, The Netherlands) under the project PT13698. | en_EN |
dc.language | Inglés | es_ES |
dc.publisher | Elsevier | es_ES |
dc.relation.ispartof | Chemometrics and Intelligent Laboratory Systems | es_ES |
dc.rights | Reserva de todos los derechos | es_ES |
dc.subject | Kernel-based techniques | es_ES |
dc.subject | Batch process monitoring | es_ES |
dc.subject | Pseudo-sample projection | es_ES |
dc.subject | Contribution plots | es_ES |
dc.subject | Fault detection | es_ES |
dc.subject | Fault diagnosis | es_ES |
dc.subject.classification | ESTADISTICA E INVESTIGACION OPERATIVA | es_ES |
dc.title | Pseudo-sample based contribution plots: innovative tools for fault diagnosis in kernel-based batch process monitoring | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.1016/j.chemolab.2015.09.013 | |
dc.relation.projectID | info:eu-repo/grantAgreement/MICINN//DPI2011-28112-C04-02/ES/MONITORIZACION, INFERENCIA, OPTIMIZACION Y CONTROL MULTI-ESCALA: DE CELULAS A BIORREACTORES. (MULTISCALES)/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/Shell Global Solutions International//PT13698/ | es_ES |
dc.rights.accessRights | Abierto | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Departamento de Estadística e Investigación Operativa Aplicadas y Calidad - Departament d'Estadística i Investigació Operativa Aplicades i Qualitat | es_ES |
dc.description.bibliographicCitation | Vitale, R.; Noord, OED.; Ferrer Riquelme, AJ. (2015). Pseudo-sample based contribution plots: innovative tools for fault diagnosis in kernel-based batch process monitoring. Chemometrics and Intelligent Laboratory Systems. 149:40-52. https://doi.org/10.1016/j.chemolab.2015.09.013 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | https://dx.doi.org/10.1016/j.chemolab.2015.09.013 | es_ES |
dc.description.upvformatpinicio | 40 | es_ES |
dc.description.upvformatpfin | 52 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 149 | es_ES |
dc.relation.senia | 302630 | es_ES |
dc.identifier.eissn | 1873-3239 | |
dc.contributor.funder | Ministerio de Ciencia e Innovación | es_ES |
dc.contributor.funder | Shell Global Solutions International | es_ES |