基于γ光子的工业件内部成像质量优化研究  

Research on Optimization of Internal Imaging Quality of Industrial Parts Based onγ-photons

作　　者：马柏林 姚敏[1] 王明[1] 刘铭 陈舒熠 MA Bolin;YAO Min;WANG Ming;LIU Ming;CHEN Shuyi(College of Automation Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing 211106,China)

机构地区：[1]南京航空航天大学自动化学院,江苏南京211106

出　　处：《机械制造与自动化》2025年第1期7-10,共4页Machine Building & Automation

基　　金：国家自然科学基金面上项目(62071229);航空科学基金项目(2020Z060052001);南京航空航天大学研究生科研与实践创新计划项目(xcxjh20220331)。

摘　　要：针对利用γ光子对工业零部件内部进行成像的图像空间分辨率较低以及边缘模糊等问题,在传统MLEM算法的基础上提出一种EP-MLEM重建算法。通过在重建的每一次迭代过程中进行优化来提高图像的质量。设计一组工业多通管仿真模型进行仿真,并分别对传统MLEM算法和改进的EP-MLEM算法重建后的图像进行图像质量评价。仿真实验表明:EP-MLEM算法重建图像的PSNR和SSIM分别由21.1434和0.6158提升到了23.1383和0.7198,EP-MLEM算法在边缘表现方面强于传统MLEM算法。In order to solve the problems of low spatial resolution and blurred edges of the images used in the internal imaging of industrial parts byγ-photons,this paper proposes an EP-MLEM reconstruction algorithm based on the traditional MLEM algorithm,which can improve the image quality by optimizing each iteration of the reconstruction.A set of industrial multi-tube simulation models is designed and simulated,and the image quality of the reconstructed image is evaluated by the traditional MLEM algorithm and the improved EP-MLEM algorithm respectively.The simulation results show that the PSNR and SSIM of the image reconstructed by EP-MLEM algorithm increase from 21.1434 and 0.6158 to 23.1383 and 0.7198 respectively,among which EP-MLEM algorithm is better than traditional one in edge performance.

关 键 词：γ光子 无损检测 软件设计 图像处理 质量优化 

分 类 号：TB302.5[一般工业技术—材料科学与工程]