基于电磁层析成像的金属缺陷稀疏成像方法

Defects detection based on electromagnetic tomography for sparse imaging method

采用电磁层析成像(electromagnetic tomography,EMT)技术实现对金属缺陷的可视化,克服了传统的检测技术无法对缺陷进行可视化的不足。首先设计了一种新型的平面EMT传感器,其次根据缺陷分布的稀疏性,提出了l1正则化稀疏成像算法。该算法能够有效避免传统的l2正则化算法带来的过度光滑的问题,成像更加精确。最后为证明该算法相对于l2正则化算法的优越性,进行了仿真和实验。仿真和实验结果均表明l1正则化稀疏成像算法能够有效提高缺陷图像的重建质量和精度。

Electromagnetic tomography （EMT） technology is used to realize the visualization of metal defects, which overcomes the lack of visualization of traditional testing technology. Firstly, a new planar sensor is designed. Secondly, according to the sparsity of defect distribution, the l1 regularized sparse imaging algorithm is proposed. The l1 regularization algorithm effectively overcomes the excessive smooth problem associated with traditional 12 regularization algorithm, whose imaging results are more accurate. Finally, in order to further prove the superiority of the new algorithm compared with l2 regularization algorithm, the simulation and experiment are conducted. The results show that sparse imaging algorithm can effectively improve the quality and accuracy of the defects images.