基于改进MRNSD算法的电阻抗层析成像

电阻抗层析成像（EIT）作为一种新兴的碳纤维增强复合材料（CFRP）无损检测方法，具有成本低、无辐射、可视化等优点，受到研究者广泛关注。EIT逆问题具有严重的病态性，通常采用正则化算法改善成像质量。基于修正残差范数最陡下降法（MRNSD），利用其在减少图像伪影和保持边界信息方面的优势，针对该算法存在的半收敛性和抗噪声效果差等问题，采用预处理和软闭值方法对MRNSD算法进行改进。通过仿真和实验，对比所提改进算法与几种常用算法的成像效果。结果表明，所提算法有效提高了EIT图像质量和抗噪声能力，并且实现了最佳迭代次数的自动更新，有利于推动EIT方法在CFRP损伤检测中的实际应用。 

Electrical impedance tomography based on improved MRNSD algorithm

Electrical Impedance Tomography (EIT), as a new nondestructive testing method for Carbon Fiber Reinforced Polymer (CFRP), has attracted extensive attention due to its low cost, non-radiation and visualization. Considering the serious ill-posedness of EIT inverse problem, regularization algorithm is usually used to improve the image quality. Based on the Modified Residual Norm Steepest Descent (MRNSD) algorithm, using its advantages in reducing image artifacts and maintaining boundary information, the MRNSD algorithm is improved by preprocessing and soft closed value method to solve the problems of semi-convergence and poor anti-noise effect of the algorithm. Through simulation and experiment, the imaging effects of the improved algorithm and several common algorithms are compared. The results show that the algorithm improves the image quality and anti-noise ability of EIT effectively, and achieves the automatic update of the optimal iteration times, which is conducive to promoting the practical application of EIT method in CFRP damage detection.