Using Vibration Analysis to Detect Failure of Bearings

Abstract

This research aims at setting a methodology to identify failures in bearings in industrial equipment by using predictive technologies. This will allow the detection of early failures of bearings in industrial equipment by identifying bearing forcing frequencies. Predictive technology was used to analyze vibration. The scope of this study covers rotating equipment in industrial plants, which will be developed in a stationary rotating unit. Failures in bearings appear progressively and are associated with working conditions. These may be expressed through signals that develop gradually depending on the bearing condition. For this study, a SKF 1211 EK bearing supported on a SKF – SNL 511-609 was used as a sample. This experimental research used a VibXpert II vibration collector and a VIB 6.142 piezoelectric sensor. For information analysis purposes, an Omnitrend V.2.92 software was used. The main findings of the work show the identification of failure frequencies in bearings, taking into account the programming of the measurement frequency range and the signal resolution prior to the measurement. As a conclusion, a methodology is needed to monitor the condition of the bearings, which may be based on measuring the acceleration amplitude and the spectral signal of the acceleration enveloping.