Rolling element bearings are important parts of rotating machineries. Any defect in their elements causes vibration and damage. Many vibration signal analysis techniques are available for detection and diagnosis of defects in machineries. In time domain vibration analysis techniques, various statistical parameters such as RMS, crest factor, skewness, kurtosis etc. are used for defect detection in bearings. Bearing related parameters like defect type, defect size, shaft speed, radial load etc. affect the bearing vibrations. In this paper, the effects of change in bearing radial load on various time-domain statistical parameters are analyzed. New combination of indicators like Kurtosis × RMS, Kurtosis × Peak, RMS × Peak and new indicators developed by researchers TALAF and THIKAT are analyzed for change in radial load on bearing. Also the effect of outer race defect in bearing on statistical parameters is analyzed. In this paper, the bearing defect data sets with outer and inner race defects provided by Society for Machinery Failure Prevention Technology are used. The results show that these parameters can be used as condition indicators for early fault detection in bearings.
In this study, the effects of the evolution of bearing outer race defect size and increase in speed on the vibration characteristics of a shaft-bearing system under unbalanced conditions. The contact stiffness between the races and the balls is considered as a series of springs is also incorporated in the model. Hertzian contact deformation theory is used to obtain the contact stiffness. This model considers the contact deformation between the balls and the races, the additional displacement between the balls and the inner race due to radial clearance, and due to defect geometry. The maximum possible radial displacement of the ball into the defect is calculated analytically using the groove radius, ball radius and defect diameter. The rectangular function is used for modelling the defect. MATLAB codes are developed for modelling the shaft-bearing system and for solving the differential equations of motion using the Runge-Kutta method. The vibration responses obtained by modelling and by experimentation show similar vibration characteristics. The investigation shows that the values of statistical parameters initially increase with the increase in defect size and then decrease with a further increase in defect size. While peak and RMS increase with the speed and crest factor and kurtosis decrease with an increase in speed. Peak is more sensitive for diagnosing spalls on outer race and its evolution. This study helps as an effective diagnosis of antifriction bearings having spalls on the outer race under unbalanced conditions.
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