Research on Image Reconstruction Algorithm Based on FOA Optimization for Detecting Aluminum Plate Flaw

Abstract

Electromagnetic tomography (EMT) can be used for metal flaw detection and defect visualization. This paper focuses on image reconstruction algorithm for detecting aluminum plate flaw. Firstly, A planar electromagnetic sensor array is designed and the sensitivity matrix is obtained. Then the Fruit Fly Optimization Algorithm (FOA) was applied to optimize the sensitivity matrix. This optimization operation can reduce the condition number and increase the morbidity degree of sensitivity matrix. Secondly, based on the traditional Landweber iterative algorithm, a new modified Landweber iterative algorithm is proposed through appending an additional regularization term into the constructed objective functional of the inverse problem of electromagnetic tomography. Finally, the modified Landweber iterative algorithm and several traditional algorithms are used for image reconstruction of round defects, long-crack defects and mixed defects. The comparison of the simulation results of different algorithms can illustrate that applying FOA to the optimization of the sensitivity matrix and the modified Landweber iterative algorithm can improve the quality of the reconstructed images. The simulation results show that using EMT technology for aluminum plate flaw detection can effectively realize defect location, classification and visualization.