Bearing Spall Size Estimation Under Varying Speed Conditions

Accurate estimation of spall size in rolling element bearings is critical for effective diagnostics and prognostics in rotating machinery. Traditional methods often struggle with generalization due to noise and speed variability. This work addresses these limitations by proposing a novel approach that leverages trends in vibration measurements over time and introduces a speed-normalized condition indicator. Building on prior work, we model the bearing fault signal as a periodic pulse wave and derive a Fourier-based representation that links harmonic magnitudes to spall size. We then introduce a normalization technique using harmonic speed ratios to eliminate the influence of the system’s transfer function. Experimental validation using controlled lab data confirms the method’s ability to preserve signal extrema and improve generalizability over different speeds, offering a promising path toward scalable, real-world bearing health monitoring.