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An improved methodology of melt pool monitoring of direct energy deposition processes

Robert Sampson, Robert Lancaster Orcid Logo, Mark Sutcliffe, David Carswell, Carl Hauser, Josh Barras

Optics & Laser Technology, Volume: 127, Start page: 106194

Swansea University Author: Robert Lancaster Orcid Logo

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Abstract

Additive manufacturing processes have previously benefited from the introduction of melt pool dimensioning systems. These typically measure melt pool width by performing binary thresholds and highlighting edges using common edge detection algorithms. Melt pool monitoring systems have been successful...

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Published in: Optics & Laser Technology
ISSN: 0030-3992
Published: Elsevier BV 2020
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa53716
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Abstract: Additive manufacturing processes have previously benefited from the introduction of melt pool dimensioning systems. These typically measure melt pool width by performing binary thresholds and highlighting edges using common edge detection algorithms. Melt pool monitoring systems have been successfully used to develop control systems and enhance process understanding. This paper presents an improved machine vision technique to enhance images in melt pool monitoring systems. Enhanced images contain features that indicate true melt pool edges. The research highlights potential flaws in more established emissivity-based image processing algorithms and a new image processing technique is developed. The new technique produced improved accuracy and performed melt pool measurements independent of emissivity values.
Keywords: Direct energy deposition, Melt pool monitoring, Machine vision, Image processing
Funders: UKRI, EP/H022309/1
Start Page: 106194