The quantitative diagnosis of localized faults, specifically accurate defect size estimation, is crucial for evaluating the degradation of rolling bearings and predicting their remaining useful life. Traditional methods rely on identifying the entry and exit points of rolling elements. However, precisely locating the exit point is challenging, as it is often masked by system noise. To overcome this limitation, this paper proposes a computational estimation method. The proposed method utilizes the distinct entry point and the trailing edge impact point in the acceleration signal. By calculating the sinking depth and deriving the path for the rolling element to climb out of the defect, the overall defect size is estimated. To validate the proposed method, a dedicated experimental test rig was developed to synchronously acquire acceleration and strain signals. The characteristics in the strain signal provide an accurate physical baseline for the actual entry and exit events. Experimental results demonstrate that the estimated defect sizes are highly consistent with the actual physical dimensions. The proposed method offers a highly reliable and accurate quantitative approach for bearing defect evaluation in industrial applications.

Rolling bearing; Quantitative diagnosis; Strain analysis; Acceleration response.