Regularization Inversion Method And Experimental Research On Magnetic Flux Leakage Detection Of Ferromagnetic Materials

Magnetic flux leakage detection has been widely studied and applied as one of the main methods for non-destructive testing of ferromagnetic materials.The problem of identification of defects by magnetic flux leakage detection belongs to the inverse problem of electromagnetic field calculation.It is difficult to solve directly because of its ill-posedness.Therefore,most of the research on the magnetic flux leakage detection method avoids the direct solution to the inverse problem,but adopts the method of search and matching.In this paper,the principle of magnetic flux leakage detection is analyzed.Based on the forward model of magnetic dipole unit integration,the method of mixed regularization is used to solve the optimal approximate solution of the corresponding inversion model,which provides a feasible way for directly solving the inverse problem of magnetic flux leakage detection.Laid the foundation for subsequent research.Firstly,this paper builds a two-dimensional cross-section model in COMSOL to analyze the characteristics and influencing factors of magnetic flux leakage signals,verified that MFL signal can reflect the defect information.Three-dimensional modeling and simulation of DC and AC magnetization methods are provided to provide reference for the construction of the magnetization device in the experimental platform.Then,the magnetization characteristics of the ferromagnetic material are simulated and analyzed.The distribution of the x component of the magnetization in the two-dimensional section can reflect the defect information.That is to solve the magnetization intensity x component of ferromagnetic material(Mx)is the core idea of defect inversion,which provides a theoretical basis for magnetic flux leakage detection.Secondly,based on the forward model of magnetic dipole unit integration,the corresponding inversion model is given.Due to the ill-posedness of the inverse problem,the existence,uniqueness and stability of the solution may not be satisfied.The regularization method is used to process the best approximate solution to approximate the true value.Comparing and selecting among various regularization methods and parameter selection methods,combined with simulation analysis,it is verified that the solution calculated by the hybrid regularization method can reflect the shape and size of defects.Finally,based on the median filtering algorithm,a multi-stage filtering algorithm suitable for magnetic flux leakage signal processing is proposed.The 2-level improved median filtering algorithm is used to eliminate the high-frequency noise that may exist in the magnetic flux leakage signal,and then the 2-level median filtering is performed to eliminate the influence of the low-frequency baseline drift.The experimental platform is built to collect the magnetic flux leakage signal and experiments on the filtering algorithm and the regularization inversion algorithm are carried out.It is verified that the filtering algorithm has good noise reduction effect on the original magnetic flux leakage signal,and also verifies the effectiveness and accuracy of the inversion algorithm in practical application environment.