Browsing by Author "Van den Eynde, Simon"

Now showing items 1-10 of 10

    • Assessing the efficiency of Laser-Induced Breakdown Spectroscopy (LIBS) based sorting of post-consumer aluminium scrap 

      Van den Eynde, Simon; Diaz-Romero, Dillam; Engelen, Bart; Zaplana Agut, Isiah; Peeters, Jef R. (Elsevier, 2022)
      Article
      Open Access
      The aluminium Twitch fraction of a Belgian recycling facility could be further sorted by implementing Laser-Induced Breakdown Spectroscopy (LIBS). To achieve this goal, the presented research identifies commercially ...

    • Classification of aluminum scrap by laser induced breakdown spectroscopy (LIBS) and RGB + D image fusion using deep learning approaches 

      Diaz-Romero, Dillam; Van den Eynde, Simon; Zaplana Agut, Isiah; Sterkens, Wouter; Goedemé, Toon; Peeters, Jef R. (2023-03)
      Article
      Restricted access - publisher's policy
      Integrating multi-sensor systems to sort and monitor complex waste streams is one of the most recent innovations in the recycling industry. The complementary strengths of Laser-Induced Breakdown Spectroscopy (LIBS) and ...

    • Deep learning regression for quantitative LIBS analysis 

      Van den Eynde, Simon; Diaz-Romero, Dillam; Zaplana Agut, Isiah; Peeters, Jef R. (2023-02)
      Article
      Restricted access - publisher's policy
      One of the most promising innovation strategies for sorting and recycling post-consumer aluminium scrap is using quantitative Laser-Induced Breakdown Spectroscopy (LIBS) analysis. However, existing methods to estimate ...

    • Enhanced plastic recycling using RGB+depth fusion with massFaster and massMask R-CNN 

      Diaz-Romero, Dillam; Zaplana Agut, Isiah; Van den Eynde, Simon; Sterkens, Wouter; Goedemé, Toon; Peeters, Jef R. (Institute of Electrical and Electronics Engineers (IEEE), 2022)
      Conference report
      Open Access
      The rapid increase in waste generation from electrical and electronic equipment (WEEE) has created the need for more advanced sensor-based systems to sort this complex type of waste. Therefore, this study proposes a method ...

    • Evaluating the effectiveness of density-based sorting of plastics from WEEE and ELVs 

      Van den Eynde, Simon; Waumans, Stijn; Dimas, Theodoros; Díaz-Romero, Dillam Jossue; Zaplana Agut, Isiah; Peeters, Jef R. (2024-10)
      Article
      Restricted access - publisher's policy
      Density-based sorting is the most commonly applied method to sort plastic waste from Electrical and Electronic Equipment (WEEE) and End-of-Life Vehicles (ELVs). Therefore, density-based sorting processes have a large ...

    • Forecasting global aluminium flows to demonstrate the need for improved sorting and recycling methods 

      Van den Eynde, Simon; Bracquené, Ellen; Diaz-Romero, Dillam; Zaplana Agut, Isiah; Engelen, Bart; Duflou, Joost R.; Peeters, Jef R. (2022-01)
      Article
      Open Access
      The probable emergence of a global aluminium scrap surplus in the coming decade is one of the main incentives for the aluminium recycling industry to invest in new methods and technologies to collect, sort and recycle ...

    • Quantification of alloying elements in steel targets: The LIBS 2022 regression contest 

      Képes, Erik; Vrábel, Jakub; Siozos, Panagiotis; Pinon, Victor; Pavlidis, Pavlos; Anglos, Demetrios; Chen, Tong; Sun, Lanxiang; Lu, Guanghui; Diaz-Romero, Dillam; Van den Eynde, Simon; Zaplana Agut, Isiah; Peeters, Jef R.; Kana, Václav; Zádera, Antonín; Palleschi, Vincenzo; De Giacomo, Alessandro; Porízka, Pavel; Kaiser, Jozef (2023-08)
      Article
      Restricted access - publisher's policy
      We present the results of the regression contest organized for the LIBS 2022 conference. While the motivation and design of the contest are briefly presented, the work focuses on the methodologies of the three best-performing ...

    • Real-time classification of aluminum metal scrap with laser-induced breakdown spectroscopy using deep and other machine learning approaches 

      Diaz-Romero, Dillam; Van den Eynde, Simon; Sterkens, Wouter; Zaplana Agut, Isiah; Goedemé, Toon; Peeters, Jef R. (2022-10)
      Article
      Open Access
      In the recycling industry, the use of deep spectral convolutional networks for the purpose of material classification and composition estimation is still limited, despite the great opportunities of these techniques. In ...

    • Simultaneous mass estimation and class classification of scrap metals using deep learning 

      Diaz-Romero, Dillam; Van den Eynde, Simon; Sterkens, Wouter; Engelen, Bart; Zaplana Agut, Isiah; Dewulf, Wim; Goedemé, Toon; Peeters, Jef R. (2022-06)
      Article
      Open Access
      While deep learning has helped improve the performance of classification, object detection, and segmentation in recycling, its potential for mass prediction has not yet been explored. Therefore, this study proposes a system ...

    • Techno-economic assessment of robotic sorting of aluminium scrap 

      Engelen, Bart; De Marelle, Dieter; Van den Eynde, Simon; Peeters, Jef R.; Zaplana Agut, Isiah; Kellens, Karel (Elsevier, 2022)
      Article
      Open Access
      Due to shifting material use in several sectors, such as the automotive sector, the demand for wrought aluminium alloys is significantly increasing. Because of their low weight and desirable mechanical properties, wrought ...