A 3-D Imaging Method for Local Shallow Defects on the Surface of Ferromagnetic Materials

Abstract

Local shallow defects on the surface of ferromagnetic materials are difficult to detect and quantify. Imaging of this kind of defects benefits to evaluate the deterioration rate. However, traditional nondestructive testing (NDT) methods have some limitations in detection sensitivity and spatial sizing resolution. To resolve this problem, a 3-D imaging method based on the law of magnetic circuit is proposed, which has a high signal-to-noise ratio (SNR) and high spatial resolution in quantization. Based on this method, a novel sensor consisting of a ring magnet, a T-shaped yoke, and a sensor array is designed, which achieves imaging defects in all directions with the same sensitivity. Three typical defects, including pit, cylindrical, and conical defects, are simulated to explore the relationship between the difference value of the magnetic flux density and the sizes (depth and radius) of these typical defects. Then, the defect reconstruction algorithm is proposed. Furthermore, we analyze the factors that affect the sensor including the relative position of the sensor and the defect, the sensor’s lift-off, and tilt. In addition, the sensor’s imaging ability to more complex defects is explored. Finally, the experimental study carried out verifies our designed sensor.