EXPERIMENTAL DETECTION OF LOCALIZED SURFACE DEFECTS IN BALL BEARINGS USING VIBRATION ANALYSIS

Abstract

Experimental Detection of Localized Surface Defects in Ball Bearings Using Vibration Analysis Bearings play a crucial role in the functioning of rotating machinery. Any failure of this critical component may cause severe disturbance to production and can lead to human injures. Condition Monitoring tools are needed to assure the healthy state of rolling element bearings during the operation. This study aimed at the monitoring of bearing health condition, based on vibration measurement. For that purpose, an appropriate test rig was designed, manufactured and tuned to accommodate the test bearings. In particular, an innovative solution for rapid mounting and dismounting of bearings on the supporting shaft was tested and used successfully in the first phase. In a second phase, tiny circular defects were seeded on outer and inner rings of similar bearings, by using the principle of Electro-Discharge Machining. The defects sizes in this investigation ranged from 0.35 mm up to 3 mm. All tested bearings had the same testing conditions. In the last phase of the project, a healthy bearing (without any defect) was installed on the test rig, and vibration measurements were taken to serve as reference data later. Each damaged bearing was installed on the test rig, and vibration measurements were performed again. Several MATLAB codes were used for recording and analyzing the experimental data. The results obtained from this work clearly show that different parameters could be extracted from time domain and frequency domain. These parameters were found to be sensitive to the growth of defects sizes in different extent, which allows the assessment of bearing health condition. In time domain, the most sensitive parameters were found to be the kurtosis and the peak amplitude. In addition to the conventional time-domain parameters, which are commonly used by vibration practitioners, two new time-domain parameters were introduced for the first time in this research. They were named as SIANA and INTHAR. Both of them demonstrated high sensitivity to the detection of growth in bearing defects sizes. In the frequency domain, the second and third harmonics of ball pass frequencies on inner and outer rings were found to be the most sensitive parameters. In general, the indicators extracted from the frequency domain seem to be more sensitive than time domain parameters to the evolution of degradation inside the bearing. The Envelope Detection (ED) was also used in this study as a possible technique to track the increase of damage extent inside bearings. Compared with direct spectrum, this approach allowed for better visualization of BPFO and BPFI. Furthermore, the use of ED was found to filter the electrical frequencies on the signal, which were hiding the real signature of defects.