Accurate Defect Quantification in Small-Diameter Elbows Using Magnetic Flux Leakage Internal Inspection

This paper presents an improved method for defect quantification in small-diameter elbow pipes using magnetic flux leakage (MFL) internal inspection. The complex geometry of elbow pipes significantly affects the MFL signals due to changes in curvature and lift-off. To address this challenge, we propose a novel approach that leverages three-axis MFL data to extract key defect features, including peak values, peak areas, and peak energies of axial and radial MFL components. Based on these features, a linear regression model is developed for defect quantification in small-diameter elbows. Furthermore, we introduce a lift-off correction factor to improve the accuracy of the quantification process. By analyzing the MFL data characteristics of various elbow defects, we establish a comprehensive defect feature database that enables the quantification of defect length, depth, and width. Experimental results demonstrate that the proposed approach, incorporating the lift-off correction factor, effectively reduces the quantification error to within 0-5.5mm, meeting the requirements for engineering applications. This advancement contributes to a more reliable and accurate MFL internal inspection technique for small-diameter elbows, facilitating better pipeline integrity management.