RESEARCH PAPER
Evaluation procedure for blowing machine monitoring and predicting bearing SKFNU6322 failure by power spectral density
| 1 | Sustainable Mining Engineering Research Group. Department of Mining, Mechanic, Energetic and Construction Engineering. Higher Technical School of Engineering, University of Huelva, 21007 Huelva, Spain |
| 2 | Department of Water, Mining and Environment. Scientific and Technological Centre of Huelva, University of Huelva, 21007 Huelva, Spain |
Publication date: 2021-09-30
Eksploatacja i Niezawodność – Maintenance and Reliability 2021;23(3):522–529
HIGHLIGHTS
- Comparative study of characteristic frequencies in terms of Power Spectral Density.
- Monitoring of blower unit and the SKFNU322 bearing.
- A new predictive maintenance protocol has been develop.
- The method used allows reducing from 6 control points to one.
KEYWORDS
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 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
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