液晶与显示2024，Vol.39Issue(1)：59-68,10.DOI:10.37188/CJLCD.2023-0088
基于密集连接和多尺度池化的X射线焊缝缺陷分割方法
X-ray weld defect detection method based on dense connection and multi-scale pooling
摘要
Abstract
In order to solve the problems of low segmentation accuracy and fuzzy boundary information of weld defects in X-ray films,this paper proposes an improved Dilated_Pooling_Unet(DP_Unet)network segmentation model.First of all,the codec information extraction module DP_block is added between up and down sampling,aiming to preserve the original defect semantic information to the greatest extent and reduce the loss caused by continuous convolution and pooling operations after down sampling.In addition,the GAM attention mechanism is added to the model to focus on welding.The seam defect part can effectively improve the learning ability of defect feature channels and reduce the influence of background noise.Finally,a hybrid loss function combining binary cross entropy and DiceLoss is proposed to solve the problems of unbalanced positive and negative data during network training.The experimental dataset is composed of the public dataset GDX-ray defect dataset.Experiments show that the method proposed in this paper has a good performance on the GDX-ray dataset,the Dice value reaches 93.45%,which are significantly improved compared with the baseline algorithm.This method has good segmentation performance,is superior to traditional segmentation algorithms,and effectively improves the segmentation accuracy of negative weld defects.关键词
焊接检测/缺陷分割/DP_Unet/注意力机制Key words
welding detection/defect segmentation/DP_Unet/attention mechanism分类
能源科技引用本文复制引用
张勇,王鹏,吕志刚,邸若海,李晓艳,李亮亮..基于密集连接和多尺度池化的X射线焊缝缺陷分割方法[J].液晶与显示,2024,39(1):59-68,10.基金项目
国家自然科学基金(No.62171360) （No.62171360）
2022年度陕西高校青年创新团队项目 （）
2023年陕西省高校工程研究中心 （）
西安市军民两用智能测评技术重点实验室 （）
陕西省电子设备智能测试与可靠性评估工程技术研究中心 （）
山东省智慧交通重点实验室(筹)Supported by National Natural Science Foundation of China(No.62171360) （筹）
2022 Shaanxi University Youth Innovation Team Project （）
2023 Shaanxi University Engineering Research Center （）
Xi'an Key Laboratory of In-telligent Evaluation Technology for Military and Civilian Use （）
Shaanxi Province Electronic Equipment Intelli-gent Testing and Reliability Assessment Engineering Technology Research Center （）
Shandong Intelligent Transportation Key Laboratory(Preparatory) （Preparatory）
