Characterization of Particle Shape of Nickel-Based Superalloy Powders Using Image Processing Techniques

In order to achieve quality control of nickel-based superalloy powders, it is necessary to quantitatively characterize the particle shape. This paper introduces how the image processing techniques were used to quantitatively evaluate the particle shape and its distribution. Firstly, the appropriate edge extraction operator was determined by multiple comparisons of processing effect of six edge extraction operators. It was found that the morphological processing technology, being similar to the watershed algorithm, demonstrated strong applicability for edge extraction. Secondly, eight shape descriptors were calculated and verified by standard graphics to ensure the accuracy of image processing algorithms. By monitoring single particle, it was found that the image processing algorithms can accurately distinguish the spherical particle from the satellite particle, and the shape descriptors change in an obvious manner. Finally, the probability density distributions of eight shape descriptors were demonstrated and compared. The results show that the image processing techniques can effectively characterize the particle shape and its distribution, which provides a methodological basis for the characterization of superalloy powders and theoretical guidance for the adjustment of atomization process. By mathematically fitting, a relationship was found between the mean shape descriptors and the angle of repose (AOR). Therefore, the method can be used to obtain the average value of shape descriptors, and then establish the relationship between the average shape descriptors and powder flowability, which can predict the process performance of powder and the performance during 3D printing.