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dc.contributor.authorCastilla Gutiérrez, Javier 
dc.contributor.authorFortes Garrido, Juan Carlos 
dc.contributor.authorDávila Martín, José Miguel 
dc.contributor.authorGrande Gil, José Antonio 
dc.date.accessioned2021-11-05T13:22:49Z
dc.date.available2021-11-05T13:22:49Z
dc.date.issued2021
dc.identifier.citationCastilla-Gutiérrez J, Fortes Garrido JC, Davila Martín JM, Grande Gil JA. Evaluation procedure for blowing machine monitoring and predicting bearing SKFNU6322 failure by power spectral density. Eksploatacja i Niezawodnosc – Maintenance and Reliability 2021; 23 (3): 522–529, http://doi.org/10.17531/ein.2021.3.13es_ES
dc.identifier.issn1507-2711
dc.identifier.urihttp://hdl.handle.net/10272/20201
dc.description.abstractThis work shows the results of the comparative study of characteristic frequencies in terms of Power Spectral Density (PSD) or RMS generated by a blower unit and the SKFNU322 bearing. Data is collected following ISO 10816, using Emonitor software and with speed values in RMS to avoid high and low frequency signal masking. Bearing failure is the main cause of operational shutdown in industrial sites. The difficulty of prediction is the type of breakage and the high number of variables involved. Monitoring and analysing all the vari- ables of the SKFNU322 bearing and those of machine operation for 15 years allowed to de- velop a new predictive maintenance protocol. This method makes it possible to reduce from 6 control points to one, and to determine which of the 42 variables is the most incidental in the correct operation, so equipment performance and efficiency is improved, contributing to increased economic profitability. The tests were carried out on a 500 kW unit of power and It was shown that the rotation of the equipment itself caused the most generating variable of vibrational energy.es_ES
dc.language.isoenges_ES
dc.publisherPolish Maintenance Societyes_ES
dc.relation.isversionofPublisher’s version
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 España*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/*
dc.subject.otherVibrationes_ES
dc.subject.otherBearing failurees_ES
dc.subject.otherDiagnosticses_ES
dc.subject.otherFailure analysises_ES
dc.subject.otherPower spectral densityes_ES
dc.titleEvaluation procedure for blowing machine monitoring and predicting bearing SKFNU6322 failure by power spectral densityes_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.identifier.doi10.17531/ein.2021.3.13
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES
dc.subject.unesco33 Ciencias Tecnológicases_ES


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