The magnetic flux leakage (MFL) method is commonly used in the nondestructive evaluation (NDE) of gun barrels. The key point of MFL testing is to estimate the crack geometry parameters based on the measured signal. Th...The magnetic flux leakage (MFL) method is commonly used in the nondestructive evaluation (NDE) of gun barrels. The key point of MFL testing is to estimate the crack geometry parameters based on the measured signal. The analysis of magnetic leakage fields can be obtained by solving Maxwell’s equations using finite element method (FEM). The radial component of magnetic flux density is measured in MFL testing. The peak-peak value, the separation distance between positive and negative peaks of signal and the lift-off value of Hall-sensor are used as the main features of every sample. This paper establishes the multi-regression equations related to the width (the depth) of crack and the main characteristic values. The regression model is tested by use of the magnetic leakage data. The experimental results indicate that the regression equations can accurately predict the 2-D defect geometry parameters and the MFL quantitative testing can be achieved.展开更多
基金National Nature Science Found of China(50175109)Science Fund of Ordnance Engineering College in China
文摘The magnetic flux leakage (MFL) method is commonly used in the nondestructive evaluation (NDE) of gun barrels. The key point of MFL testing is to estimate the crack geometry parameters based on the measured signal. The analysis of magnetic leakage fields can be obtained by solving Maxwell’s equations using finite element method (FEM). The radial component of magnetic flux density is measured in MFL testing. The peak-peak value, the separation distance between positive and negative peaks of signal and the lift-off value of Hall-sensor are used as the main features of every sample. This paper establishes the multi-regression equations related to the width (the depth) of crack and the main characteristic values. The regression model is tested by use of the magnetic leakage data. The experimental results indicate that the regression equations can accurately predict the 2-D defect geometry parameters and the MFL quantitative testing can be achieved.