3D Reconstructing of Arbitrary Defects with Magnetic Flux Leakage Testing Signals

By detecting and processing the Magnetic Flux Leakage (MFL) signals to identify and estimate the defects in ferromagnetic materials or structures, for example, in the steel pipelines, the so called Magnetic Flux Leakage Testing (MFLT) technology has been widely used in industry. However, the existing MFLT technology is suitable for locating the defects and rough estimating their sizes based on enormous sample data, incapable to image their Three-Dimensional (3D) shapes and precise estimate their sizes, while the physical model associating the defect geometry details and the MFL signals were still unclear. In this study, (1) the effects of an actual 3D defect are taken into account by introducing a new concept, Depth Field over a surface, i.e., a matrix of loss of material on the testing surface of a structure; (2) the governing equations for the depth field and the MFL signals are derived; (3) an algorithm to reconstruct the 3D defect or the depth field based on the governing equations is developed. This new method does not require huge amount of pulling-test data for calibration purpose as the existing MFLT technology used in industry, and it has been verified via a series of tests with various defects of different shapes in pipelines, the results indicate it is valid for 3D defect reconstruction with high accuracy.