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| Naji, M. |
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| Motta, Antonella |
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| Aletan, Dirar |
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| Mohamed, Tarek |
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| Ertürk, Emre |
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| Taccardi, Nicola |
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| Petrov, R. H. | Madrid |
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| Alshaaer, Mazen | Brussels |
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| Bih, L. |
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| Casati, R. |
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| Kočí, Jan | Prague |
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| Kalteremidou, Kalliopi-Artemi | Brussels |
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| Azam, Siraj |
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| Ospanova, Alyiya |
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| Ali, M. A. |
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| Rančić, M. |
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| Ollier, Nadège |
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| Azevedo, Nuno Monteiro |
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| Landes, Michael |
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| Rignanese, Gian-Marco |
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Arroud, Galid
Vrije Universiteit Brussel
in Cooperation with on an Cooperation-Score of 37%
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Publications (5/5 displayed)
- 2022FPGA-based visual melt-pool monitoring with pyrometer correlation for geometry and temperature measurement during Laser Metal Depositioncitations
- 2020Microstructure and corrosion behavior of 316L stainless steel prepared using different additive manufacturing methodscitations
- 2020Offline powder-gas nozzle jet characterization for coaxial laser-based Directed Energy Depositioncitations
- 2019On the Influence of Capillary-Based Structural Health Monitoring on Fatigue Crack Initiation and Propagation in Straight Lugscitations
- 2016Reconstruction of impacts on a composite plate using fiber Bragg gratings (FBG) and inverse methodscitations
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document
FPGA-based visual melt-pool monitoring with pyrometer correlation for geometry and temperature measurement during Laser Metal Deposition
Abstract
Laser metal deposition is an additive manufacturing technology where<br/>the process parameters greatly influence the product quality and<br/>geometry. Therefore, it is generally concluded that real-time control and<br/>monitoring of the process is required to deliver quality parts. However,<br/>during the building process it is only possible to control the liquid state of<br/>the melt-pool. Monitoring of the melt-pool typically involves image<br/>processing and comes with an associated computational cost. CPU-based<br/>systems are limited in the real-time field due to their slower response<br/>than their FPGA counterparts for parallel computing and related latency.<br/>This paper presents an FPGA-based vision system that extracts<br/>geometric and intensity statistical features in real-time of the melt-pool<br/>based on a low-cost VNIR (Visible and Near-Infrared) camera. The<br/>extraction of features of the melt-pool is achieved by a thresholding<br/>approach and a 2D blob analysis using image moments. A pyrometer is<br/>used synchronously with the camera to measure simultaneously the<br/>temperature in the melt-pool. The observed melt-pool shape and<br/>intensity features are compared to the temperature values, and the<br/>results are discussed and correlated.