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A Novel Peak Detection Algorithm for Use in the Study of Machining Chip Segmentation



Eric P. Whitenton


The study of how metal is deformed (how it flows) as parts are machined yields important insights into the metal cutting process. Recent improvements in both high-speed digital imaging and image processing software promise to improve our understanding of the tool-workpiece interface and verify the accuracy of finite element modeling simulations. This will ultimately allow industry to improve machining processes and make parts faster an at less cost. This report describes the design and results of an automated system to estimate chip segmentation frequency. The system uses high-speed imaging of machining chips combined with displacement vector mapping and processing. As part of the displacement vector map processing, a novel, efficient peak detection algorithm was developed. It minimizes a priori assumptions about the data and yields information that assists in uncertainty analysis of the peak detection process. However, further work needs to be performed before a rigorous uncertainty analysis may be completed.
Hood College Computer Science Department
Report Number


chip morphology, high-speed video, orthogonal cutting, segmentation


Whitenton, E. (2007), A Novel Peak Detection Algorithm for Use in the Study of Machining Chip Segmentation, Hood College Computer Science Department, [online], and (Accessed April 12, 2024)
Created March 1, 2007, Updated February 19, 2017