As the weakest point of the pipeline, the weld seam is prone to various internal defects and has great safety risks, so it is necessary to conduct a weld seam inspection. In addition, accurately detecting small-sized defects from high-resolution and low-contrast X-ray images is still a challenging task. Therefore, this paper proposes a defect detection method for high-resolution weld images, including three steps: welded extraction, weld restructuring, and defect detection. Because the resolution of the original image is high and the defect features are mainly concentrated in the weld area, it is not easy to directly defect detection. Firstly, a new irregular long weld extraction algorithm based on wandering Gaussian was designed. Secondly, because the existing welding seams aspect ratio is large and the information loss of conventional compression methods is serious, a new feature reorganization method was provided to maximize the effective information of the weld. Finally, a new method of welding defects detection method based on cross-layer feature fusion has been redesigned to take into efficiency and accuracy. The experiments show that the proposed method achieves the best detection performance on the public GDXray dataset compared with other advanced defect detection methods, from which it can locate the weld defects automatically and fast with high accuracy. It provides an effective solution for high-resolution weld defect detection.

焊缝作为管道最薄弱的部位，容易产生各种内部缺陷，安全隐患很大，因此有必要进行焊缝检测。此外，从高分辨率和低对比度的 X 射线图像中准确检测小尺寸缺陷仍然是一项具有挑战性的任务。因此，本文提出了一种高分辨率焊缝图像的缺陷检测方法，包括三个步骤：焊缝提取、焊缝重构和缺陷检测。由于原始图像分辨率高，缺陷特征主要集中在焊缝区域，不易直接进行缺陷检测。首先，设计了一种新的基于漂移高斯的不规则长焊缝提取算法。第二，针对现有焊缝纵横比大，传统压缩方法信息丢失严重的问题，提出了一种新的特征重组方法，最大限度地利用焊缝的有效信息。最后，重新设计了一种基于跨层特征融合的焊接缺陷检测方法，以兼顾效率和准确性。实验表明，与其他先进的缺陷检测方法相比，该方法在公共 GDXray 数据集上实现了最佳检测性能，可以自动、快速、高精度地定位焊缝缺陷。它为高分辨率焊缝缺陷检测提供了有效的解决方案。重新设计了一种基于跨层特征融合的焊接缺陷检测方法，兼顾效率和准确性。实验表明，与其他先进的缺陷检测方法相比，该方法在公共 GDXray 数据集上实现了最佳检测性能，可以自动、快速、高精度地定位焊缝缺陷。它为高分辨率焊缝缺陷检测提供了有效的解决方案。重新设计了一种基于跨层特征融合的焊接缺陷检测方法，兼顾效率和准确性。实验表明，与其他先进的缺陷检测方法相比，该方法在公共 GDXray 数据集上实现了最佳检测性能，可以自动、快速、高精度地定位焊缝缺陷。它为高分辨率焊缝缺陷检测提供了有效的解决方案。