A Simulation and Experimental Study Investigating 2D Magnetic Flux Leakage (MFL) for Defects in Reinforcing Steel

The study examines magnetic flux leakage signals (Bx, By) within D19 sized rebars in two dimensions. An economically designed test setup incorporating permanent magnets was used to collect magnetic flux leakage at the defect location. The numerical simulation was performed using COMSOL Multiphysics on a 2D finite element model. This study also attempts to enhance defect analysis by using the MFL signals (Bx, By). As defect width increases, the x-component of the signal (Bx) increases, and with depth, the y-component (By) increases. Even though depth and width interact in signal appearance, the overall amplitude variation was sufficient to predict the defect area. R2=0.9079 indicates a higher coefficient of regression for x-component (Bx) amplitudes in defect areas. A positive correlation between defect position, geometry, and shape was found

Quantitative Study on Corrosion of Steel Strands Based on Self-Magnetic Flux Leakage

This paper proposed a new computing method to quantitatively and non-destructively determine the corrosion of steel strands by analyzing the self-magnetic flux leakage (SMFL) signals from them. The magnetic dipole model and three growth models (Logistic model, Exponential model, and Linear model) were proposed to theoretically analyze the characteristic value of SMFL. Then, the experimental study on the corrosion detection by the magnetic sensor was carried out. The setup of the magnetic scanning device and signal collection method were also introduced. The results show that the Logistic Growth model is verified as the optimal model for calculating the magnetic field with good fitting effects. Combined with the experimental data analysis, the amplitudes of the calculated values (BxL(x,z) curves) agree with the measured values in general. This method provides significant application prospects for the evaluation of the corrosion and the residual bearing capacity of steel strand