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Proceedings Paper

Detection and visualization of porosity in industrial CT scans of aluminum die castings
Author(s): Lee T. Andrews; Joseph W. Klingler; Jeffery A. Schindler; Michael S. Begeman; Donald Farron; Bobbi J. Vaughan; Bud Riggs; John Cestaro
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Paper Abstract

During the production of aluminum die castings, regions of porosity are created in the resultant part. These regions may or may not have an effect on the overall quality of the part depending on the location of the porosity. If the porosity is located in areas which do not require machining, such as drilling and tapping, the porosity will not affect the performance of the part and therefore does not result in a reject. However, if the porosity provides a pathway for passage of air or liquid from one chamber to another the porosity will result in a defective part. Porosity is measured in a variety of ways such as fluoroscopy, pressurization in a water tank and other techniques of nondestructive testing (NDT). This project was undertaken to evaluate if industrial computed tomography (CT) scanning could detect porosity and to measure the connectivity of detected porosity to determine if the part is a 'leaker.' Scans were taken of aluminum die castings and then analyzed to determine if the porosity present could be detected with this method. Three-dimensional gray scale mathematical morphology algorithms were developed to extract regions of porosity while maintaining the geometric integrity of the data. Once the regions of porosity were found, connectivity analysis was performed to determine if the porosity provided a path between chambers of the castings. Visualization of the porosity contained within the casting was accomplished using apE (Animation Production Environment) from the Ohio Supercomputer Graphics Project. Using transparency and color, the regions of porosity can easily be seen within the 3D renderings of the part. Due to the large quantity of data the morphological analysis and renderings were done on a Cray Y/MP supercomputer at the Ohio Supercomputer Center. This process shows promise in the design of new castings and in the quality control of existing production.

Paper Details

Date Published: 1 June 1991
PDF: 11 pages
Proc. SPIE 1459, Extracting Meaning from Complex Data: Processing, Display, Interaction II, (1 June 1991); doi: 10.1117/12.44389
Show Author Affiliations
Lee T. Andrews, Medical College of Ohio (United States)
Joseph W. Klingler, Medical College of Ohio (United States)
Jeffery A. Schindler, Medical College of Ohio (United States)
Michael S. Begeman, Medical College of Ohio (United States)
Donald Farron, Edison Industrial Systems Ctr. (United States)
Bobbi J. Vaughan, Edison Industrial Systems Ctr. (United States)
Bud Riggs, Doehler-Jarvis Corp. (United States)
John Cestaro, Doehler-Jarvis Corp. (United States)


Published in SPIE Proceedings Vol. 1459:
Extracting Meaning from Complex Data: Processing, Display, Interaction II
Edward J. Farrell, Editor(s)

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