Fatigue life prediction of steel components with local surface damage using ultrasonic imaging and critical distance theory.

Pitting corrosion is a prominent form of localized surface damage that can significantly accelerate fatigue failure in metal components due to stress concentration effects. Ultrasonic testing has proven to be a powerful tool for detecting the early initiation of localized corrosion. However, most previous research has focused solely on assessing corrosion severity, lacking a quantitative link between corrosion-induced damage and structural fatigue life. To bridge this gap, this study proposes a strategy to predict the fatigue life of Q690E steel components affected by localized corrosion by integrating ultrasonic imaging with fatigue life estimation. A simplified semi-elliptical notch is employed to simulate localized corrosion pits in this study. The key novelty of this work lies in correlating corrosion-induced damage with fatigue life by reconstructing the defect geometry using the total focusing imaging method (TFM). TFM is leveraged to visualize and quantify corrosion pit geometry, providing the necessary input for fatigue analysis. The theory of critical distance (TCD) is then applied to calculate the effective stress and predict fatigue life. Numerical and experimental studies validate this approach, demonstrating that TFM can accurately characterize pit depth and aspect ratio for defects with widths and heights equal to or greater than one wavelength. The predicted fatigue life falls within the four scatter bands of experimental fatigue life data, confirming that this method provides a reliable estimation of fatigue life in components affected by localized corrosion.