Experimental diagnostics of ball bearings using statistical and spectral methods

Vibration measurements and signal analysis is widely used for condition monitoring of ball bearings as their vibration signature reveals important information about the defect development within them. Time domain analysis of vibration signature such as peak-to-peak amplitude, root mean square, Crest factor and kurtosis indicates defects in ball bearings. However, these measures do not specify the position and/or nature of the defects. Each defect produces characteristic vibrations in ball bearings. Hence, examining the vibration spectrum may deliver information on the type of defects. In this paper a test rig is designed and a pair of brand new commercial ball bearings is installed. The bearings run throughout their lifespan under constant speed and loading conditions. Vibration signatures produced are recorded and statistical measures are calculated during the test. When anomalies are detected in the statistical measures, vibration spectra are obtained and examined to determine where the defect is on the running surfaces. At the end of the test, the ball bearings are disassembled in order to take microscopic photos of the defects.