Abstract
Steel cleanliness as measured by nonmetallic inclusion content in steel plays a major role in affecting bearing durability. A high-fidelity virtual bearing life test model was developed to predict the impact of inclusions on bearing fatigue life. This model analyzes distributions of inclusion size, shape, orientation, and location, and computes stress alterations to bearing material due to inclusions and the resulting life reduction. Comparisons between model predictions and experimental test results were made, confirming the validity of the model. Parametric studies were conducted to explore the effects of inclusion counts, inclusion size distributions, and the effect of overall bearing size on bearing life. A regression equation was proposed based on simulation results, linking the bearing life reduction factor (LRF) to the accumulative inclusion length within the stressed volume under contact load.
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