Magnetic flux leakage testing defect reconstruction method based on improved artificial bee colony algorithm

Abstract

The invention relates to a magnetic flux leakage testing defect reconstruction method based on an improved artificial bee colony algorithm. According to the method, a radial basis function neural network is used as a forward model, and an error square sum of a magnetic flux leakage signal predicted by the forward model and an actually measured magnetic flux leakage signal is used as a target function to improve the artificial bee colony algorithm; a current individual optimal solution and a global optimal solution are introduced to accelerate algorithm convergence speed; the improved artificial bee colony algorithm is used as an iterative algorithm to solve a reconstruction problem, and the finally obtained global optimal solution is a reconstructed defect outline. The magnetic flux leakage testing defect reconstruction method based on the improved artificial bee colony algorithm improves speed and precision of magnetic flux leakage testing defect reconstruction.

Description

technical field [0001] The invention relates to a magnetic flux leakage detection technology, in particular to a defect reconstruction method of magnetic flux leakage detection based on an improved artificial bee colony algorithm. Background technique [0002] Magnetic flux leakage testing is one of the commonly used non-destructive testing methods for ferromagnetic materials. It has the advantages of simple principle, strong online detection capability, and is not affected by oil stains on the surface of materials and other non-magnetic coverings. Magnetic flux leakage detection includes two aspects: forward modeling and inversion. Magnetic flux leakage defect contour reconstruction refers to the reconstruction of defect contour or geometric parameters from the detected magnetic flux leakage signal, which is the key to magnetic flux leakage detection and evaluation. At present, the research on MFL inversion at home and abroad mainly includes neural network method and optimi...

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Problems solved by technology

[0004] Aiming at the problem of how to improve the artificial bee colony algorithm and apply it to the reconstruction of magnetic flux leakage defects, the present invention proposes a method for reconstruction of magnetic flux leakage detection defects based on the improved artificial bee colony algorithm. The current optimal solution pbest and The global optimal solution gbest is introduced into the ABC algorithm, and the improved ABC algorithm is applied to the defect reconstruction of magnetic flux leakage detection. The improved algorithm can improve the reconstruction accuracy and reduce the calculation time

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