Control and prediction protocol for bearing failure through spectral power density

Abstract

This paper aims to analyse the results of the comparative study of the characteristic frequencies, in terms of Power Spectral Density (PSD), generated by an SKF6322 bearing in a rotational blower. Among all the analysed frequencies, we have focused on the ones generated by the shaft rotation speed, the one on the blades and the ones of the SKF6322 bearing, such as the tracks, the cage and the balls. For this study, we followed the ISO 10816 criteria, both in the sampling part and in the data analysis, using the speed values in terms of PSD, which improves the results in both high and low frequencies. This study can be used to predict the performance of bearings and their future failure, determining the most decisive frequency, the one with the highest incidence and the relative influence of each one on the different positions and monitoring coordinate axes. This procedure can be applied to improve the predictive maintenance protocol in order to improve the performance, efficiency and reliability of the equipment with bearings in their systems.

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

“…Other studies determine that the turning variable of the machine generates more incidence in POS4V. In the case of the blades, the axial position would be the most important [2,3]. In the Table 9 shows the comparison of the three frequencies.…”

Comparable analysis of PID controller settings in order to ensure reliable operation of active foil bearings

“…In order to solve many problems concerning the operation and properties of foil bearings, FEM simulations are carried out by Peng et al [44], among other activities, by coupling various fields such as mechanical and thermal [57]. Another way to improve the performance, efficiency and reliability of equipment with bearings in their systems is the use of an appropriate procedure to improve the predictive maintenance protocol [12]. The approach allows to increase the number of monthly tests, improving predictability, reliability, maintenance and production at the same cost.…”