VOLUME SEGMENTATION BY POST-PROCESSING DATA FROM SIMULATION OF SOLIDIFICATION IN THE METAL CASTING PROCESS

In the process of interpreting simulation results,new post-processing techniques are developed.This work presents a post-processing method that analyzes the solidification pattern formed by simulation of the solidification process of molten metal in a mold to produce shaped castings.Simulations generally involve numerical solutions of differential equations which are discretized by dividing the three-dimensional computational domain into small finite volume elements using a 3D grid.The locations of the grid points and values of the solidification time at these locations are used to divide the spatial data into 3D sections such that starting from a hotspot location within the section that has high solidification time,there is a gradient outwards with lower values of solidification time.Each section is assumed to be fed by one or more feeders that must freeze only after the section has solidified completely.The volume of a feeder can be determined from the volume of the section it is supposed to feed.The volume and surface area of sections are determined approximately to calculate feeder size and dimensions.The post-processing algorithm is a simulation-based quantitative approach to feeder design which in conventional foundry practice has been more of an art than science.It is also general enough for use in other 3D segmentation applications.

Bin-scanning:Segmentation of X-ray CT volume of binned parts using Morse skeleton graph of distance transform

X-ray CT scanners,due to the transmissive nature of X-rays,have enabled the non-destructive evaluation of industrial products,even inside their bodies.In light of its effectiveness,this study introduces a new approach to accelerate the inspection of many mechanical parts with the same shape in a bin.The input to this problem is a volumetric image(i.e.,CT volume)of many parts obtained by a single CT scan.We need to segment the parts in the volume to inspect each of them;however,random postures and dense contacts of the parts prohibit part segmentation using traditional template matching.To address this problem,we convert both the scanned volumetric images of the template and the binned parts to simpler graph structures and solve a subgraph matching problem to segment the parts.We perform a distance transform to convert the CT volume into a distance field.Then,we construct a graph based on Morse theory,in which graph nodes are located at the extremum points of the distance field.The experimental evaluation demonstrates that our fully automatic approach can detect target parts appropriately,even for a heap of 50 parts.Moreover,the overall computation can be performed in approximately 30 min for a large CT volume of approximately 2000×2000×1000 voxels.

Displaying of Details in Subvoxel Accuracy

Under the volume segmentation in voxel space, a lot of details, some fine and thin objects, are ignored. In order to accurately display these details, this paper has developed a methodology for volume segmentation in subvoxel space. In the subvoxel space, most of the 'bridges' between adjacent layers are broken down.Based on the subvoxel space, an automatic segmentation algorithm reserving details is discussed. After segmentation, volume data in subvoxel space are reduced to original voxel space. Thus, the details with width of only one or several voxels are extracted and displayed.