【摘要】 环焊缝缺陷的类型识别对于长输管线管道焊缝质量评价以及管道服役寿命评估具有重要意义。由于不同类型缺陷的射线检测图像具有特征差异小、对比度低等特征，现有缺陷类型识别方法所提取的特征表征能力不足，其准确性及可信性难以满足行业需求。为此，提出了一种缺陷领域特征提取与Transformer融合的焊缝缺陷类型识别方法。基于环焊缝缺陷评定技术人员的知识及缺陷领域特征，从缺陷几何特征、缺陷位置特征以及缺陷背景区域特征3个方面定义了14个特征，用于实现不同类型缺陷的特征表征；以Transformer网络为基础，融合上述14个特征提出深度可调节的缺陷类型识别模型与方法。以企业实际环焊缝缺陷数据对模型进行验证。结果表明，与ResNet50网络相比，所提模型对于未熔合、未焊透缺陷，分类精度分别提高18.2%和14.3%;对于咬边和内凹2种形状缺陷，分类精度达到90%以上。证明所提方法可以有效提高缺陷类型识别准确率，可将其扩展到射线检测铸造缺陷、TOFD检测焊缝缺陷识别领域。更多还原

【Abstract】 The identification of types of girth weld defects is of great significance for the quality evaluation of welding seams in long-distance pipeline and the evaluation of pipeline service life.Due to the small feature differences and low contrast in radiographic inspection images of different types of defects, the features extracted by the existing defect type identification methods have insufficient characterization capability, and their accuracy and credibility are difficult to meet industry requirements.Therefore, a weld defect type identification method based on defect domain feature extraction and Transformer fusion was proposed.First, based on the knowledge of technical personnel for girth weld defect evaluation and the defect domain features, 14 features were defined from 3 aspects such as defect geometric features, defect location features and defect background areal features to achieve feature characterization of different types of defects.Second, based on the Transformer model, the above 14 features were fused to present a depth adjustable defect type identification model and method.Finally, the actual girth weld defect data from the enterprise were used to verify the model.The results show that the model has improved the classification accuracy by 18.2% and 14.3% respectively compared to the ResNet50 model for lack of fusion and lack of penetration defects, while for the undercut and concave defects, the classification accuracy reaches over 90%,Proving that this method can effectively improve the defect type identification accuracy, and can be extended to the type identification field such as radiographic inspection of casting defects and TOFD inspection of weld defects.更多还原