Evaluation procedure for blowing machine monitoring and predicting bearing SKFNU6322 failure by power spectral density

• Autorzy: Castilla-Gutiérrez Javier , Fortes Garrido Juan Carlos , Davila Martín Jose Miguel , Grande Gil Jose Antonio

Identyfikatory

DOI

10.17531/ein.2021.3.13

• Języki publikacji: EN

Abstrakty

EN

This 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 variables of the SKFNU322 bearing and those of machine operation for 15 years allowed to develop 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.

Słowa kluczowe

EN

vibration; bearing failures; diagnostics; failure analysis; power spectral density

• Wydawca: Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne
• Czasopismo: Eksploatacja i Niezawodność
• Rocznik: 2021
• Tom: Vol. 23, no. 3
• Strony: 522--529
• Opis fizyczny: Bibliogr. 43 poz., rys., tab.

Twórcy

autor

Castilla-Gutiérrez Javier

• Sustainable Mining Engineering Research Group. Department of Mining, Mechanic, Energetic and Construction Engineering. Higher Technical School of Engineering, University of Huelva, 21007 Huelva, Spain

autor

Fortes Garrido Juan Carlos

• Department of Water, Mining and Environment. Scientific and Technological Centre of Huelva, University of Huelva, 21007 Huelva, Spain
• Sustainable Mining Engineering Research Group. Department of Mining, Mechanic, Energetic and Construction Engineering. Higher Technical School of Engineering, University of Huelva, 21007 Huelva, Spain

autor

Davila Martín Jose Miguel

• Department of Water, Mining and Environment. Scientific and Technological Centre of Huelva, University of Huelva, 21007 Huelva, Spain
• Sustainable Mining Engineering Research Group. Department of Mining, Mechanic, Energetic and Construction Engineering. Higher Technical School of Engineering, University of Huelva, 21007 Huelva, Spain

autor

Grande Gil Jose Antonio

• Department of Water, Mining and Environment. Scientific and Technological Centre of Huelva, University of Huelva, 21007 Huelva, Spain
• Sustainable Mining Engineering Research Group. Department of Mining, Mechanic, Energetic and Construction Engineering. Higher Technical School of Engineering, University of Huelva, 21007 Huelva, Spain

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).