轴类超声检测的波束扩散成像*

大型轴类工件安装完成后通常只能从其端面进行检测,危害性的裂纹类缺陷不易检出,针对上述问题,本文提出了轴类对象基于波束扩散的端面网格化超声检测层析成像方法,搭建了轴类超声检测试验平台,在端面对其内部的平底孔缺陷进行检测,基于波束扩散设计叠加算法进行数据处理,然后根据结果重构出代表每个深度内部信息的伪彩色横截面图像,以方便快速识别内部缺陷位置和范围。与常规方法对比得出,基于波束扩散的叠加算法处理数据成像质量更佳,提高缺陷检测灵敏度达到12dB以上。

Image method of shaft ultrasonic detection based on beam diffusion

After the installation of large shaft workpieces, it is usually only possible to detect from the end faces, and the dangerous crack defects are not easy to detect. In view of the above problems, this paper proposes a beam-based end-grid ultrasonic detection tomography method based on beam diffusion. A shaft ultrasonic testing platform was built, and the flat bottom hole defects were detected at the end face. The data was processed based on the beam diffusion design superposition algorithm, and then the pseudo color cross section representing the internal information of each depth was reconstructed according to the result. Images to facilitate quick identification of internal defect locations and ranges. Compared with the conventional method, the beam diffusion based superposition algorithm processes the data imaging quality better, and improves the defect detection sensitivity to more than 12dB.