Automatic Recognition of Dendritic Solidification Structures: DenMap

Abstract

Dendrites are the predominant solidification structures in directionally solidified alloys and control the maximum length scale for segregation. The conventional industrial method for identification of dendrite cores and primary dendrite spacing is performed by time-consuming laborious manual measurement. In this work we developed a novel DenMap image processing and pattern recognition algorithm to identify dendritic cores. Systematic row scan with a specially selected template image over an image of interest is applied via a normalised cross-correlation algorithm. The DenMap algorithm locates the exact dendritic core position with a 98% accuracy for a batch of SEM images of typical as-cast CMSX-4® microstructures in under 90 s per image. Such accuracy is achieved due to a sequence of specially selected image pre-processing methods. Coupled with statistical analysis the model has the potential to gather large quantities of structural data accurately and rapidly, allowing for optimisation and quality control of industrial processes to improve mechanical and creep performance of materials.

On Directional Dendritic Growth and Primary Spacing—A Review

“…Following this, multiple new imaging and diffraction methods have been developed to investigate the shape and orientation of grains [224,229,230]. The spatial resolution of the MCP detector is now nearly ten times smaller than the typical λ 1 length [231,232]. Therefore, neutron imaging may provide the micro-macroscopic experimental link for improving understanding of the process versus property relationships within directionally solidified bulk metallic alloys.…”

A 3D Analysis of Dendritic Solidification and Mosaicity in Ni-Based Single Crystal Superalloys

“…Therefore, there is a need to facilitate this process. It is reasonable to assume that the present approach will significantly benefit from the application of machine learning techniques, which are currently of interest in materials science, e.g., [75][76][77]. For example, neuronal networks could be applied to detect dendrites from metallographic cross sections, to retrieve their positions and to trace their growth across tomographic images.…”

On the origin of mosaicity in directionally solidified Ni-base superalloys

“…The bulk BSE sample maps were loaded into the DenMap software [37] and the exact dendrite core pixel positions were located. ̅ variation across each bulk microstructure was determined using the Shape-Limited Primary Spacing (SLPS) methodology, as described elsewhere [18].…”