Study on Automatic Identification Algorithm for X-ray Diffraction Spots of Single Crystal Superalloy

Single crystal superalloy has been widely used as hot components of aeroengine and gas turbine for its good anti-fatigue performance and high temperature creep property. At the same time, the defects like crystal off-orientation and mixed crystal would be produced during the manufacture of single crystal superalloy. Nowadays, Lane X-ray diffraction method is already widely used for nondestructive testing of these crystal defects on single crystal turbine blades all over the world. However, this method is not appropriate for mass testing as a result of its high dependency of manual identification, low efficiency and weak repeatability of the result. This article presents an automatic identification algorithm addressed on Laue X-ray diffraction spots patterns based on practical engineering needs, including pre-processing of diffraction pattern, contour detection, shape filtering of contours, and contour coincidence check. This algorithm can automatically find out spots on diffraction patterns, and offer their positions with measurement errors. Finally, the crystal orientation of the tested sample can be calculated based on these positions of spots with diffraction analysis method and so can those crystal defects on tested turbine blades sample be evaluated.