Three-dimensional magnetic flux leakage detection defect complex inversion imaging method

Abstract

The present invention provides a three-dimensional magnetic flux leakage detection defect complex inversion imaging method which comprises a step of obtaining an imaging area from a pipeline to be detected, a step of scanning the pipeline to be detected to obtain a magnetic flux leakage field detection value, a step of constructing a reverse radial basis function neural network model and inputting the magnetic flux leakage field detection value to obtain the initial value of a defect profile parameter, a step of constructing a positive finite element calculation model, inputting the initial value of a defect profile parameter, and obtaining a magnetic flux leakage field detection value, a step of judging whether the error between the magnetic flux leakage field detection value and a magnetic flux leakage field preset value is smaller than or equal to a preset error threshold, if so, realizing defect imaging according to the initial value of the defect profile parameter, and if not, updating the initial value of the defect profile parameter, and inputting the finite element calculation model to carry out iterative calculation again until the error is smaller than or equal to the preset error threshold. According to the method, the problem of excessive iterations in a conventional closed loop iterative method is reduced, and the method has the advantages of high practicability, good stability and high imaging precision.

Description

technical field [0001] The invention relates to the technical field of nondestructive testing, in particular to a composite inversion imaging method for defects in three-dimensional magnetic flux leakage testing. Background technique [0002] Magnetic flux leakage testing is a more commonly used non-destructive testing method, which is widely used in the quality testing and safety monitoring of ferromagnetic materials such as oil and gas pipelines, storage tank floors, and steel wire ropes. In recent years, with the continuous improvement and improvement of defect quantification technology, people hope that the distribution of pipeline corrosion defects can be transformed into graphics and images that can be directly recognized by the naked eye, so as to realize defect imaging. However, due to the complex nonlinear relationship between defect shape and magnetic flux leakage signal, defect imaging has become a difficult and hot spot in the current research of magnetic flux le...

AI Technical Summary

Problems solved by technology

For example, the MFL defect reconstruction method based on the cuckoo search and particle filter hybrid algorithm can accurately realize the defect contour reconstruction to a certain extent, especially reduce signal noise and improve the robustness of the iterative method to noise, but still It is the two-dimensional reconstruction of the defect contour, and the calculation model is too complicated and the efficiency is not high

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