MFL (magnetic flux leakage) testing defect three-dimensional imaging method based on magnetic charge distribution reconstruction algorithm

Abstract

The invention belongs to the technical field of material defect detection, and particularly relates to an MFL (magnetic flux leakage) testing defect three-dimensional imaging method based on a magnetic charge distribution reconstruction algorithm. The method mainly comprises steps as follows: (1), defect boundary information and positive and negative magnetic charge distribution areas are divided on the basis of a two-dimensional magnetic charge distribution reconstruction algorithm; (2), the analysis relation between a defect depth field and a leakage magnetic field is established, and iteration of defect depth distribution is performed through magnetic leakage signals (B). Quantum calculation of a three-dimensional shape with any defect can be realized during MFL testing, and the quantitative accuracy of the MFL testing method is improved during testing and evaluation of defects.

Description

Technical field: [0001] The invention belongs to the technical field of material defect detection, in particular to a three-dimensional imaging method for magnetic flux leakage detection defects based on a magnetic charge distribution reconstruction algorithm. technical background: [0002] Magnetic flux leakage detection (Magnetic Flux Leakage, MFL) has the advantages of strong ability to identify defects online, no strict cleanliness requirements for the detection surface, large penetration depth, simple equipment structure, easy operation, fast detection speed, and can work in complex environments. At present, one of the main methods for non-destructive detection of material missing defects in ferromagnetic pipe fittings, plates, and rods in service is widely used in the detection of defects in energy oil and gas pipelines, oil storage tank bottoms, traffic rails, and key ferromagnetic components of large and heavy equipment. In non-destructive testing. It is of great si...

AI Technical Summary

Problems solved by technology

The latest international literature introduces a combined method of using the leakage magnetic field cloud image to correspond to defect width and length boundary information + boundary constraint depth reconstruction method. Since the leakage magnetic field cloud image is affected by the detection lift-off, the result of using the leakage magnetic field cloud image to correspond to the defect width and length boundary information is rough. It affects the accuracy of the next step of deep iterative reconstruction; the rationality of artificially increasing constraints during deep iterative reconstruction needs to be paid attention to, so the accuracy of 3D quantification of defects is not high

Images