人工智能技术在射线检测底片评定系统中的应用  

Application of artificial intelligence technology in radiographic inspection film evaluation system

作　　者：邓聪 罗伟坚[1] 李绪丰 DENG Cong;LUO Weijian;LI Xufeng(Guangdong Institude of Special Equipment Inspection and Research,Foshan 528251,China;School of Mechanical and Automotive Engineering,South China University of Technology,Guangzhou 510640,China)

机构地区：[1]广东省特种设备检测研究院,佛山528251 [2]华南理工大学机械与汽车工程学院,广州510640

出　　处：《无损检测》2022年第8期65-68,73,共5页Nondestructive Testing

基　　金：国家市场监督管理总局科技计划项目(2020MK087)。

摘　　要：将基于大数据的人工智能技术与射线检测底片评定相结合,实现了对数字化底片中无效底片与重复底片的智能筛选以及对焊缝缺陷的智能识别和评定,不仅有效改善了传统检测方法的不足,还提升了检测质量和现场管理水平。对深度学习领域中的图像分割技术、焊缝缺陷分类识别以及焊缝综合信息提取等关键技术进行了阐述,并对其核心算法模块进行了重点介绍,同时,通过实际工程项目对人工智能评片系统的可行性和稳定性进行了验证,有望为该系统后续大规模应用提供一些参考。With the combination of radiographic evaluation system and artificial intelligence technique based on big data, the intelligent filter of invalid films and duplicate films and the intelligent identification and evaluation of weld defects were realized. It not only effectively improves the deficiency of the method of traditional inspection, but also enhances the quality of inspection and management. In this paper, the gordian methods of image segmentation model in the field of deep learning and classification and identification of weld defects and extraction of comprehensive information of weld and the modules of core algorithm were described. And the feasibility and stability of the radiographic evaluation system were verified by practical engineering projects, which could be a reference for the subsequent large-scale application.

关 键 词：人工智能 射线检测 焊缝缺陷 深度学习 

分 类 号：TG115.28[金属学及工艺—物理冶金]