Research on the force-magnetic coupling of steel wire and defect evaluation based on self-magnetic flux leakage effect

Abstract

As an important load-bearing component, wire rope is widely used in engineering structures. It is significant to conduct nondestructive testing on the wire rope and ensure its safe operation. The magnetic signal inspection based on the self-magnetic flux leakage (SMFL) effect can effectively identify the location of defects. However, the current research on the magnetic signal of defects with the influence of various factors is insufficient. Based on the SMFL inspection of defective steel wire under tensile load, it puts forward an approach to evaluate the defect through the peak-valley value of the normal component Hp(y) of the magnetic signal. Then the numerical simulation of force-magnetic coupling with COMSOL Multiphysics is conducted. Finally, the additive model is applied to analyze the factors affecting the magnetic characteristic parameters. The results show that the peak-valley values of Hp(y) with different sizes of defects increase first and then decrease with the increase of load, which can be used to evaluate the stress state of the defective steel wire; According to the nonlinear force-magnetic coupling model based on the thermodynamic relation under the constant weak magnetic field, the SMFL field of the defective steel wire can be calculated through the magnetization constitutive relationship using the representative stress of the refined domains at the defect; By comparing and verifying the results simulated and experimental, the additive model is further introduced to quantitatively analyze the magnetic signal of the defect considering the combined action of the defect depth h, the defect width w and the external load F. The defect depth h has a significant influence on the magnetic signal characteristics, which can be estimated by the additive model with determined w and F. This study is expected to provide some references for the quantitative analysis of defects under loading.