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Diagnostics of machining center by means of neural networks

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dc.title Diagnostics of machining center by means of neural networks en
dc.contributor.author Skála, Radovan
dc.contributor.author Oplatková, Zuzana
dc.contributor.author Šenkeřík, Roman
dc.relation.ispartof MENDEL 2011
dc.identifier.issn 1803-3814 Scopus Sources, Sherpa/RoMEO, JCR
dc.identifier.isbn 9788021443020
dc.date.issued 2011
dc.citation.spage 207
dc.citation.epage 212
dc.event.title 17th International Conference on Soft Computing: Evolutionary Computation, Genetic Programming, Fuzzy Logic, Rough Sets, Neural Networks, Fractals, Bayesian Methods, MENDEL 2011
dc.event.location Brno
utb.event.state-en Czech Republic
utb.event.state-cs Česká republika
dc.event.sdate 2011-06-15
dc.event.edate 2011-06-17
dc.type conferenceObject
dc.language.iso en
dc.publisher Brno University of Technology
dc.subject Diagnostics en
dc.subject Machining center en
dc.subject Neural networks en
dc.description.abstract This paper deals with a usage of neural networks for diagnostics of machining center. The diagnostics of machines is very important. To discover backlash, clearance or allowance during the machine work can prevent the mass production of rejects. The aim is to propose a less expensive solution than currently sophisticated commercial software can offer. This paper will explain the diagnostics on specific machining center and its mechanical systems, currently from the point of view - whether there is or there is no error. The introduction into machining center diagnostics is followed by results carried out during simulations with usage of feed forward neural net. en
utb.faculty Faculty of Applied Informatics
dc.identifier.uri http://hdl.handle.net/10563/1004892
utb.identifier.obdid 43866938
utb.identifier.scopus 2-s2.0-84904176469
utb.identifier.wok 000302647900033
utb.source d-scopus
dc.date.accessioned 2015-06-04T12:55:54Z
dc.date.available 2015-06-04T12:55:54Z
utb.contributor.internalauthor Oplatková, Zuzana
utb.contributor.internalauthor Šenkeřík, Roman
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