Abstract
Optical belt sorters are a versatile means to sort bulk materials. In previous work, we presented a novel design of an optical belt sorter, which includes an area scan camera instead of a line scan camera. Line scan cameras, which are well-established in optical belt sorting, only allow for a single observation of each particle. Using multitarget tracking, the data of the area scan camera can be used to derive a part of the trajectory of each particle. The knowledge of the trajectories can be used to generate accurate predictions as to when and where each particle passes the separation mechanism. Accurate predictions are key to achieve high quality sorting results. The accuracy of the trajectories and the predictions heavily depends on the motion model used. In an evaluation based on a simulation that provides us with ground truth trajectories, we previously identified a bias in the temporal component of the prediction. In this paper, we analyze the simulation-based ground truth data of the motion of different bulk materials and derive models specifically tailored to the generation of accurate predictions for particles traveling on a conveyor belt. The derived models are evaluated using simulation data involving three different bulk materials. The evaluation shows that the constant velocity model and constant acceleration model can be outperformed by utilizing the similarities in the motion behavior of particles of the same type.
Zusammenfassung
Optische Bandsortierer sind vielseitige Maschinen zur Sortierung von Schüttgütern. In vorangegangenen Arbeiten haben wir ein neues Design eines optischen Bandsortierers vorgeschlagen, in dem eine Flächenkamera anstelle einer Zeilenkamera eingesetzt wird. Zeilenkameras, die in optischen Bandsortierern etabliert sind, erlauben nur eine einmalige Beobachtung eines jeden Partikels. Mithilfe von Multitarget-Tracking-Verfahren können die Daten der Flächenkamera dazu verwendet werden, einen Teil der Trajektorien der Teilchen zu bestimmen. Das Wissen über die Trajektorien kann genutzt werden, um vorherzusagen, wann und wo die Teilchen an dem Separationsmechanismus vorbeifliegen. Akkurate Vorhersagen sind essenziell, um hochqualitative Sortierergebnisse zu erzielen. Die Genauigkeit der Trajektorien und Vorhersagen hängt stark von dem eingesetzten Bewegungsmodell ab. In einer Evaluation basierend auf einer Simulation, welche die wahren Trajektorien liefert, wurde zuvor ein Bias in den Vorhersagen identifiziert. Im vorliegenden Beitrag analysieren wir die Trajektorien unterschiedlicher Schüttgüter in Simulationen und leiten Bewegungsmodelle her, die auf die Vorhersage der Bewegung von Schüttgutteilchen auf einem Förderband zurechtgeschnitten sind. Die vorgestellten Modelle werden anhand Simulationen dreier Schüttgüter evaluiert. In der Evaluation zeig sich, dass Modelle, die Ähnlichkeiten im Bewegungsverhalten gleichartiger Teilchen berücksichtigen, die Constant-Velocity- und Constant-Acceleration-Modelle in ihrer Vorhersagegenauigkeit übertreffen können.
Funding source: Bundesministerium für Wirtschaft und Energie
Award Identifier / Grant number: 18798 N
Award Identifier / Grant number: 20354 N
Funding statement: The IGF projects 18798 N and 20354 N of the research association Forschungs-Gesellschaft Verfahrens-Technik e.V. (GVT) are supported via the AiF in a program to promote the Industrial Community Research and Development (IGF) by the Federal Ministry for Economic Affairs and Energy on the basis of a resolution of the German Bundestag.
About the authors
Florian Pfaff is a postdoctoral researcher at the Intelligent Sensor-Actuator-Systems Laboratory at the Karlsruhe Institute of Technology. He obtained his diploma in 2013 and his Ph.D. in 2018, both with the highest distinction. His research interests include a variety of estimation problems such as filtering on nonlinear manifolds, multitarget tracking, and estimation in the presence of both stochastic and non-stochastic uncertainties.
Christoph Pieper is a research assistant at the Department of Energy Plant Technology at the Ruhr University Bochum. His research interests include numerical simulation of fluidized particle systems with the Discrete Element Method (DEM) and Computational Fluid Dynamics (CFD).
Georg Maier is with the Fraunhofer Institute of Optronics, System Technologies and Image Exploitation IOSB, Karlsruhe, Germany. His research interests include different aspects of image processing, in particular algorithmic aspects, with a focus on real-time capabilities.
Benjamin Noack is a senior researcher at the Intelligent Sensor-Actuator-Systems Laboratory at the Karlsruhe Institute of Technology (KIT), Germany. His research interests are in the areas of multi-sensor data fusion, distributed and decentralized Kalman filtering, combined stochastic and set-membership approaches to state estimation, and event-based systems.
Robin Gruna is research group manager at the Fraunhofer Institute of Optronics, System Technologies and Image Exploitation IOSB in Karlsruhe, Germany. His research interests include spectral imaging, machine learning, and computational imaging.
Harald Kruggel-Emden is professor and head of the department of Mechanical Process Engineering and Solids Processing at the Technical University of Berlin. His research interests include Discrete Element Modelling with coupled fluid flow, material preparation and drying technology, bulk solids handling, and chemical looping combustion.
Uwe D. Hanebeck is a chaired professor of Computer Science at the Karlsruhe Institute of Technology (KIT) in Germany and director of the Intelligent Sensor-Actuator-Systems Laboratory (ISAS). He obtained his Ph.D. degree in 1997 and his habilitation degree in 2003, both in Electrical Engineering from the Technical University in Munich, Germany. His research interests are in the areas of information fusion, nonlinear state estimation, stochastic modeling, system identification, and control with a strong emphasis on theory-driven approaches based on stochastic system theory and uncertainty models. He is author and coauthor of more than 500 publications in various high-ranking journals and conferences and an IEEE Fellow.
Siegmar Wirtz is the deputy head of the Department of Energy Plant Technology at the Ruhr University Bochum. His research interests include numerical simulation of reactive gas–solid flows, extension of commercial CFD codes, and Discrete Element Modelling with coupled fluid flow.
Viktor Scherer is the head of the Department of Energy Plant Technology at the Ruhr University Bochum. His research interests include energetic conversion of fossil fuels and biomass as well as related industrial applications and experimental and theoretical investigation of energy and high temperature processes.
Thomas Längle is adjunct professor at the Karlsruhe Institute of Technology (KIT), Karlsruhe, and the head of the business unit “Vision Based Inspection Systems” (SPR) at the Fraunhofer IOSB in Karlsruhe, Germany. His research interests include different aspects of image processing and real-time algorithms for inspection systems.
Jürgen Beyerer has been a full professor for informatics at the Institute for Anthropomatics and Robotics at the Karlsruhe Institute of Technology (KIT) since March 2004 and director of the Fraunhofer Institute of Optronics, System Technologies and Image Exploitation (IOSB) in Ettlingen, Karlsruhe, Ilmenau, Lemgo, Görlitz. He is Spokesman of the Fraunhofer Group for Defense and Security VVS and he is member of acatech, National Academy of Science and Engineering. Furthermore, he is Head of team 7 of the platform “Lernende Systeme” and Spokesman of the Competence Center Robotic Systems for Decontamination in Hazardous Environments (ROBDEKON). Research interests include automated visual inspection, signal and image processing, pattern recognition, metrology, information theory, machine learning, system theory security, autonomous systems, and automation.
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