Comprehensive Prediction Model for Analysis of Rolling Bearing Ring Waviness

The objective of this study was to identify surface geometric deviations that may adversely affect the operational properties of bearings, including vibration, noise, and service life. A comprehensive prediction model is presented that combines a fundamental trend expressed by a power function with periodic oscillations, whose influence gradually diminishes with exponential decay. The model was calibrated using the experimental data obtained from 17 industrial RA-608-338 rolling bearing rings manufactured from high-carbon, low-alloy 100Cr6 steel. An excellent goodness-of-fit (R2 exceeding 0.98) and minimal root-mean-square error (RMSE) were achieved. The proposed procedure provides a clear physical interpretation of the model’s subcomponents, while facilitating straightforward implementation in real production processes for continuous quality control and predictive maintenance purposes. This paper also includes a detailed description of the methodology, data processing, experimental results, comparison of multiple model variants, interactive visualization of the results on a logarithmic scale, and recommendations for practical application.