Non-destructive damage detection for steel pipe scaffolds using MFL-based 3D defect visualization

Magnetic flux leakage (MFL) is a commonly used non-destructive technique for diagnosing defects in steel structures. In this study, we investigate a magnetic flux leakage (MFL)-based 3D visualization approach for identifying metal loss defects and evaluating their severity, which is a major concern in various industry fields where the structural integrity of specimens is crucial. We focus specifically on small-dimensional steel pipelines and steel pipe scaffolds as target specimens, which require a consistent inspection system to maintain their healthy performance for their intended purposes. When a magnetic field encounters a small air gap created by a defect, it spreads out because the air cannot support as much magnetic field per unit volume as a magnet can. We detect and measure the MFL signal that leaks due to the metal loss using a sensor head prototype containing hall sensors, which is used to scan the steel pipeline. The measured MFL signals are used to investigate abnormalities in the targeted pipeline specimen. Once the MFL signal is collected and measured, a series of digital signal processing steps are performed to enhance the resolution and extent of the defect level. This study proposes a 3D visualization of the defect profile based on the time domain MFL data, which provides insights into how the defect occurs on the target specimen and the general location of the defect. This visualization approach offers an effective means of evaluating the severity of metal loss defects in steel structures and can help ensure the long-term structural integrity of these specimens.