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单晶高温合金展现出优越的抗疲劳性能和高温蠕变性能,广泛应用于航空发动机和燃气轮机的热端部件。但是,其制备过程中会产生晶体取向偏离、杂晶等缺陷。目前国际上已经普遍使用X射线劳埃衍射技术对单晶叶片的晶体缺陷进行无损检测,但是这种检测方法主要依赖人工识别,效率低,结果可重复性差,不适合批量化检测。本文结合工程需要,提出对劳埃衍射斑点进行自动识别的算法,主要包括衍射图样的预处理、轮廓检测、轮廓形态筛选及轮廓符合检测等。该算法能够自动检测出衍射图样上的衍射斑点,并最终给出斑点的位置坐标数据及其误差。根据衍射斑点的位置,通过衍射分析算法,计算出单晶叶片上的晶体取向,并最终对叶片的晶体缺陷给出综合评价。
Single crystal superalloy exhibits superior fatigue resistance and high temperature creep properties and is widely used in hot end components of aeroengines and gas turbines. However, its preparation process will produce crystal orientation deviation, miscellaneous crystal and other defects. At present, the X-ray Lara Diffraction (XRD) technique has been widely used in the nondestructive testing of crystal defects in single crystal leaves. However, this method mainly depends on artificial identification, which has low efficiency and poor repeatability. It is not suitable for batch inspection. In this paper, an algorithm for automatic recognition of Laue diffraction spots is proposed, which includes the preprocessing of diffraction patterns, contour detection, contour morphology screening and contour matching detection. The algorithm can automatically detect the diffraction spots on the diffraction pattern, and finally gives the location coordinates of the spots and their errors. According to the position of the diffraction spots, the crystal orientation on the single crystal blade is calculated by the diffraction analysis algorithm, and finally the comprehensive evaluation of the crystal defects of the blade is given.