量子电子学报2026，Vol.43Issue(1)：75-87,13.DOI:10.3969/j.issn.1007-5461.2026.01.006
基于改进ResNet-50算法的EMT缺陷成像方法
EMT defect imaging method based on the improved ResNet-50 algorithm
摘要
Abstract
Aiming at the problem of poor reconstructed image quality in electromagnetic tomography(EMT)for metal defect detection due to the inverse problem unsuitability and pathology,an EMT defect imaging method based on the improved ResNet-50 algorithm is proposed in this work.Firstly,by simulating and modeling the eight-coil EMT inspection system,and followed by applying an electromagnetic field to the object under test and using sensor arrays to obtain the information of electromagnetic field distribution around it,a training set is constructed and the raw voltage data are preprocessed.And then,the nonlinear mapping ability of the deep residual network is utilized to complete the learning of the training set,and the training effect is evaluated by the test set.The experiments show that the improved ResNet-50 algorithm reduces the root mean square error by 87.10%,81.63%,57.79%,and 19.11%respectively,and improves the structural similarity index by 88.87%,71.82%,16.24%,and 4.54%respectively,compared to Tikhonov regularization algorithm,Landweber iteration algorithm,VGG-16 algorithm,and improved ResNet-18 algorithm,and at the same time,can accurately restore the defect location,shape and size.Overall,the improved method significantly improves the reconstruction accuracy,quality and efficiency,confirming its superiority in EMT defect imaging.关键词
电磁计量/电磁层析成像/改进ResNet-50/缺陷成像/图像重建Key words
electromagnetic metrology/electromagnetic tomography/improved ResNet-50/defect imaging/image reconstruction分类
通用工业技术引用本文复制引用
王晋华,王明泉,路宇鹏,曹振锋,吴志成..基于改进ResNet-50算法的EMT缺陷成像方法[J].量子电子学报,2026,43(1):75-87,13.基金项目
国家自然科学基金(61171177),山西省重点研发计划(201803D121069),山西省高等学校科技创新项目(2020L0624) （61171177）
