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

Abstract

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.