Materials Map

Discover the materials research landscape. Find experts, partners, networks.

  • About
  • Privacy Policy
  • Legal Notice
  • Contact

The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

×

Materials Map under construction

The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

To Graph

1.080 Topics available

To Map

977 Locations available

693.932 PEOPLE
693.932 People People

693.932 People

Show results for 693.932 people that are selected by your search filters.

←

Page 1 of 27758

→
←

Page 1 of 0

→
PeopleLocationsStatistics
Naji, M.
  • 2
  • 13
  • 3
  • 2025
Motta, Antonella
  • 8
  • 52
  • 159
  • 2025
Aletan, Dirar
  • 1
  • 1
  • 0
  • 2025
Mohamed, Tarek
  • 1
  • 7
  • 2
  • 2025
Ertürk, Emre
  • 2
  • 3
  • 0
  • 2025
Taccardi, Nicola
  • 9
  • 81
  • 75
  • 2025
Kononenko, Denys
  • 1
  • 8
  • 2
  • 2025
Petrov, R. H.Madrid
  • 46
  • 125
  • 1k
  • 2025
Alshaaer, MazenBrussels
  • 17
  • 31
  • 172
  • 2025
Bih, L.
  • 15
  • 44
  • 145
  • 2025
Casati, R.
  • 31
  • 86
  • 661
  • 2025
Muller, Hermance
  • 1
  • 11
  • 0
  • 2025
Kočí, JanPrague
  • 28
  • 34
  • 209
  • 2025
Šuljagić, Marija
  • 10
  • 33
  • 43
  • 2025
Kalteremidou, Kalliopi-ArtemiBrussels
  • 14
  • 22
  • 158
  • 2025
Azam, Siraj
  • 1
  • 3
  • 2
  • 2025
Ospanova, Alyiya
  • 1
  • 6
  • 0
  • 2025
Blanpain, Bart
  • 568
  • 653
  • 13k
  • 2025
Ali, M. A.
  • 7
  • 75
  • 187
  • 2025
Popa, V.
  • 5
  • 12
  • 45
  • 2025
Rančić, M.
  • 2
  • 13
  • 0
  • 2025
Ollier, Nadège
  • 28
  • 75
  • 239
  • 2025
Azevedo, Nuno Monteiro
  • 4
  • 8
  • 25
  • 2025
Landes, Michael
  • 1
  • 9
  • 2
  • 2025
Rignanese, Gian-Marco
  • 15
  • 98
  • 805
  • 2025

Devesse, Wim

  • Google
  • 14
  • 14
  • 178

Vrije Universiteit Brussel

in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (14/14 displayed)

  • 2020Spatial distributed spectroscopic monitoring of melt pool and vapor plume during the laser metal deposition process2citations
  • 2020Comparison of visual and hyperspectral monitoring of the melt pool during Laser Metal Depositioncitations
  • 2019Hyperspectral and Thermal Temperature Estimation During Laser Cladding18citations
  • 2017Proof of Concept of Integrated Load Measurement in 3D Printed Structures7citations
  • 2017Model-based temperature feedback control of laser cladding using high-resolution hyperspectral imaging17citations
  • 2017Fatigue Performance of Ti-6Al-4V Additively Manufactured Specimens with Integrated Capillaries of an Embedded Structural Health Monitoring System19citations
  • 2016Hardware-in-the-loop control of additive manufacturing processes using temperature feedback42citations
  • 2016Spectroscopic monitoring and melt pool temperature estimation during the laser metal deposition process16citations
  • 2016Evaluation of the Diffuse Reflectivity Behaviour of the Melt Pool During the Laser Metal Deposition Processcitations
  • 2016Temperature Feedback Control of Laser Cladding Using High Resolution Hyperspectral Imagingcitations
  • 2015Modeling of laser beam and powder flow interaction in laser cladding using ray-tracing57citations
  • 2015Hardware-in-the-loop control of additive manufacturing processes using temperature feedbackcitations
  • 2015Spectroscopic monitoring and melt pool temperature estimation during the laser metal deposition processcitations
  • 2014Modeling of laser beam and powder flow interaction in laser cladding using ray-tracingcitations

Places of action

Chart of shared publication
Helsen, Jan
1 / 9 shared
Guillaume, Patrick
14 / 40 shared
Baere, Dieter De
13 / 26 shared
Ertveldt, Julien
1 / 16 shared
Sanchez Medina, Jorge
1 / 6 shared
Lison, Margot
2 / 2 shared
Hinderdael, Michaël
8 / 22 shared
Jardon, Zoé
1 / 12 shared
Strantza, Maria
2 / 13 shared
Graeve, Iris De
1 / 57 shared
Terryn, Herman
1 / 124 shared
Thienpont, Hugo
2 / 83 shared
Pauw, Ben De
3 / 4 shared
Smeesters, Lien
2 / 3 shared
Chart of publication period
2020
2019
2017
2016
2015
2014

Co-Authors (by relevance)

  • Helsen, Jan
  • Guillaume, Patrick
  • Baere, Dieter De
  • Ertveldt, Julien
  • Sanchez Medina, Jorge
  • Lison, Margot
  • Hinderdael, Michaël
  • Jardon, Zoé
  • Strantza, Maria
  • Graeve, Iris De
  • Terryn, Herman
  • Thienpont, Hugo
  • Pauw, Ben De
  • Smeesters, Lien
OrganizationsLocationPeople

document

Temperature Feedback Control of Laser Cladding Using High Resolution Hyperspectral Imaging

  • Guillaume, Patrick
  • Devesse, Wim
  • Hinderdael, Michaël
  • Baere, Dieter De
Abstract

Laser cladding is a technique that is frequently used for the coating and repair of metallic components. This technology can also be found in the additive manufacturing domain where it is more commonly known as direct metal deposition. The creation of freeform metallic parts using laser cladding is a promising area of research, with a lot of attention dedicated to the optimization of the process parameters and to automatic control strategies. A critical aspect of such feedback control systems is the accuracy of the sensor used for monitoring the process. This paper presents a feedback control scheme in which a hyperspectral camera is used to provide high resolution temperature information about the melt pool. A PI controller actuates the laser based on the measured temperature profile in order to maintain a constant melt pool size. Improved noise rejection properties are obtained by adding a model-based state observer to the control loop. The performance of the controller is evaluated by creating tracks with varying thicknesses on a base plate of AISI 316L stainless steel. Comparison of the on-line temperature measurements with off-line images of the tracks show that the measurements correspond very well to the true temperature profiles that were present during the process. As a result, the experiments demonstrate that the controller is able to successfully follow a given melt pool size reference with high precision.

Topics
  • Deposition
  • impedance spectroscopy
  • stainless steel
  • experiment
  • melt
  • additive manufacturing