RT Journal Article
T1 Evaluation procedure for blowing machine monitoring and predicting bearing SKFNU6322 failure by power spectral density
A1 Castilla Gutiérrez, Javier
A1 Fortes Garrido, Juan Carlos
A1 Dávila Martín, José Miguel
A1 Grande Gil, José Antonio
AB 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 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.
PB Polish Maintenance Society
SN 1507-2711
YR 2021
FD 2021
LK http://hdl.handle.net/10272/20201
UL http://hdl.handle.net/10272/20201
LA eng
NO Castilla-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.2021.3.13
DS Repositorio Institucional de la Universidad de Huelva
RD 31 may 2026