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

• Published in: Optics and laser technology Vol. 127; p. 106194
• Main Authors: Sampson, Robert, Lancaster, Robert, Sutcliffe, Mark, Carswell, David, Hauser, Carl, Barras, Josh
• Format: Journal Article
• Language: English
• Published: Kidlington Elsevier Ltd 01.07.2020; Elsevier BV
• Subjects: Algorithms; Direct energy deposition; Edge detection; Emissivity; Flaw detection; Image enhancement; Image processing; Machine vision; Melt pool monitoring; Monitoring; Monitoring systems; Machine vision; Image processing; Direct energy deposition; Melt pool monitoring
• ISSN: 0030-3992; 1879-2545
• DOI: 10.1016/j.optlastec.2020.106194

•A novel image processing technique to more accurately measure the width of a melt pool was developed.•Validation of the technique was provided through single frame analysis.•Results highlighted fundamental issues with emissivity-based edge detection methods.•New technique can create enhanced control systems and optimise deposition quality. 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.