Three-dimensional irregular defect contour reconstruction method based on improved trust region projection algorithm

Abstract

The invention relates to a three-dimensional irregular defect contour reconstruction method based on an improved trust region projection algorithm. According to the invention, a detection region is firstly selected from to-be-detected ferromagnetic materials, magnetic charge density of the detection region is calculated by using a cuckoo search algorithm, and distribution of the magnetic charge density is further utilized to construct a unit magnetic dipole band superposition model of a three-dimensional irregular shape defect; then, an estimated signal is compared with a real signal by using the unit magnetic dipole band superposition model, and a proper sampling region is selected; and finally, an improved trust region projection Levenberg-Marquart algorithm is provided for ill-posed nature of a three-dimensional irregular defect reconstruction problem, and reconstruction of an irregular defect contour is achieved. Compared with the prior art, the method does not need a large amount of magnetic flux leakage detection data, reduces the problem of too many iterations in a heuristic optimization algorithm, and achieves the higher precision of a reconstruction result.

Description

technical field [0001] The invention relates to the technical field of nondestructive testing, in particular to a three-dimensional irregular defect contour reconstruction method based on an improved trust region projection algorithm. Background technique [0002] Magnetic flux leakage detection technology is a commonly used nondestructive detection technology for damage defects of ferromagnetic materials. It has been widely used in the fields of power equipment, high-speed rail transportation and petrochemical industry, showing unique advantages and broad development prospects. Generally, in order to maintain the normal operation of power equipment, it is necessary to conduct non-destructive testing on the equipment regularly to evaluate its health status. Due to the complex nonlinear relationship between defects and magnetic flux leakage signals, the existing algorithms for magnetic flux leakage detection and defect reconstruction generally have problems such as large amou...

AI Technical Summary

Problems solved by technology

For example, using the finite element model and the genetic tabu search algorithm to update the three-dimensional defect contour, although the defect contour reconstruction can be accurately realized to a certain extent, and it is robust to noise, but the amount of calculation is too large

In addition, the multivariate least squares support vector machine algorithm is used to predict the three-dimensional defect contour. Although this method can achieve accurate contour reconstruction for a class of three-dimensional defects, it only reconstructs regular defect contours and cannot satisfy Irregular Defect Refactoring Requirements

It is also a common method to use the radial component of the magnetic flux leakage signal for higher-precision defect identification. However, this method cannot guarantee that a complete defect opening profile can be obtained every time during imaging.

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