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Characterizing material flow in sensor-based sorting systems using an instrumented particle

Charakterisierung des Materialflusses in sensorgestützten Sortiersystemen unter Verwendung eines instrumentierten Partikels
Georg Maier

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.

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, Florian Pfaff

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.

, Andrea Bittner

Andrea Bittner received the M. Sc. degree in computer science from the Karlsruhe Institute of Technology in 2017. During the final phase of her studies, she was involved in analyzing motion of bulk material by means of instrumented particles. Her research interests include analysis of large amounts of data and software engineering.

, Robin Gruna

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.

, Benjamin Noack

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.

, Harald Kruggel-Emden

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

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 480 publications in various high-ranking journals and conferences and an IEEE Fellow.

, Thomas Längle

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.

and Jürgen Beyerer

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.

Abstract

Sensor-based sorting is a well-established single particle separation technology. It has found wide application as a quality assurance and control approach in food processing, mining, and recycling. In order to assure high sorting quality, a high degree of control of the motion of individual particles contained in the material stream is required. Several system designs, which are tailored to a sorting task at hand, exist. However, the suitability of a design for a sorting task is assessed by empirical observation. The required thorough experimentation is very time consuming and labor intensive. In this paper, we propose an instrumented bulk material particle for the characterization of motion behavior of the material stream in sensor-based sorting systems. We present a hardware setup including a 9-axis absolute orientation sensor that is used for data acquisition on an experimental sorting system. The presented results show that further processing of this data yields meaningful features of the motion behavior. As an example, we acquire and process data from an experimental sorting system consisting of several submodules such as vibrating conveyor channels and a chute. It is shown that the data can be used to train a model which enables predicting the submodule of a sorting system from which an unknown data sample originates. To our best knowledge, this is the first time that this IIoT-based approach has been applied for the characterization of material flow properties in sensor-based sorting.

Zusammenfassung

Die sensorgestützte Sortierung ist eine etablierte Einzelpartikel-Trenntechnik. Sie wird vielseitig als Qualitätssicherungs- und Sichtprüfansatz in der Lebensmittelverarbeitung, im Bergbau und im Recycling eingesetzt. Um eine hohe Sortierqualität zu gewährleisten, ist ein hohes Maß an Kontrolle über die Bewegung der einzelnen im Materialstrom enthaltenen Partikel erforderlich. Es existieren mehrere Systemauslegungen, die auf eine bestimmte Sortieraufgabe zugeschnitten sind. Die Eignung einer Auslegung für eine Sortieraufgabe wird jedoch durch empirische Beobachtung beurteilt. Die hierfür erforderlichen Experimente sind sehr zeitaufwendig und arbeitsintensiv. In dieser Arbeit stellen wir ein instrumentiertes Schüttgutpartikel zur Charakterisierung des Bewegungsverhaltens des Materialstroms in sensorgestützten Sortiersystemen vor. Wir entwerfen und realisieren ein Hardware-Setup, das u. a. einen 9-Achsen-Absolut-Orientierungssensor enthält, der zur Datenerfassung auf einem experimentellen Sortiersystem verwendet wird. Die vorgestellten Ergebnisse zeigen, dass durch weitere Verarbeitung dieser Daten aussagekräftige Merkmale des Bewegungsverhaltens extrahiert werden können. Als Beispiel erfassen wir Daten von einem experimentellen Sortiersystem, das aus mehreren Komponenten wie Schwingförderrinnen und einer Rutsche besteht, und werten diese aus. Wir zeigen, dass mit den Daten ein Modell trainiert werden kann, welches eine unbekannte Datenprobe der Komponente des Sortiersystems zuordnen kann, in welchem sie aufgenommen wurde. Nach unserem besten Wissen wird dieser IIoT-basierte Ansatz zum ersten Mal für die Charakterisierung von Materialflusseigenschaften in der sensorgestützten Sortierung angewendet.

Award Identifier / Grant number: 18798 N

Award Identifier / Grant number: 20354 N

Funding statement: IGF projects 18798 N and 20354 N of research association Forschungs-Gesellschaft Verfahrens-Technik e. V. (GVT) was supported by the AiF under a program for promoting 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

Georg Maier

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.

Florian Pfaff

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.

Andrea Bittner

Andrea Bittner received the M. Sc. degree in computer science from the Karlsruhe Institute of Technology in 2017. During the final phase of her studies, she was involved in analyzing motion of bulk material by means of instrumented particles. Her research interests include analysis of large amounts of data and software engineering.

Robin Gruna

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.

Benjamin Noack

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.

Harald Kruggel-Emden

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

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 480 publications in various high-ranking journals and conferences and an IEEE Fellow.

Thomas Längle

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

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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Received: 2019-12-05
Accepted: 2020-01-17
Published Online: 2020-03-25
Published in Print: 2020-04-28

© 2020 Walter de Gruyter GmbH, Berlin/Boston

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