Vibration analysis approach for corrosion pitting detection based on SVDD and PCA

This study is focused on corrosion pitting on the raceways and ball in rolling bearings. We analyze 224 records in the time domain, and combine support vector data description (SVDD) with principal component analysis (PCA) algorithm to improve diagnostic accuracy. Experiment results show that the proposed method can achieve good accuracy based on an imbalanced dataset. The new method is thus well-suited for corrosion pitting detection in rolling bearings.