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Image-based algorithm for nozzle adhension detection in powder-fed directed-energy deposition

Paper presented at ICALEO 2019, International Congress on Applications of Lasers and Electro-Optics, October 7-10, 2019, Orlando, Florida
: Kledwig, Christian; Perfahl, Holger; Reisacher, Martin; Brückner, Frank; Bliedtner, Jens; Leyens, Christoph

2019, Paper LAM905, 6 pp.
International Congress on Applications of Lasers & Electro-Optics (ICALEO) <2019, Orlando/Fla.>
Conference Paper
Fraunhofer IWS ()
Anfrage beim Institut / Available on request from the institute

The rapidly growing technological innovation of Directed Energy Deposition (DED) leads to an increase in part complexity as well as quality and mechanical properties of manufacturable components. However, the variety of process parameters and influencing factors still requires skilled operators, who observe the machine tools. For an unobserved use of deposition welding machines, well parametrised and validated monitoring systems have to analyse the process to detect irregularities and finally initiate a machine stop. This study focuses on nozzle adhesions that frequently occur when tool or high-speed steels are processed. This effect leads to decreasing quality or ultimately to a failure of the whole welding process. In this work, we present an algorithm and the corresponding parametrisation to automatically detect nozzle adhesions based on images from a coaxial camera, integrated in the laser head. The algorithm is based on a detailed image analysis from which temporal and spatial patterns are derived. In particular, the algorithm calculates a nozzle adhesion indicator based on the heat intensity distribution in an experimentally derived shaped area on the inner nozzle boundary. It is parametrised in such a way that processcritical adhesions are detected. The algorithm was parametrised using an experimental setup with four materials: Stainless steel (X2CrNiMo17-12-2), tool steel (X35CrMoMn7-2-1), high-speed steel (HS6-5-2C) and the nickel-based alloy NiCr19NbMo.