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MULTISENSOR INTEGRATION

Real-time resource characterization.

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OVERVIEW

Optical sensors have become key to most on- and in-line scanning applications in the field of material characterization, digitalization, and monitoring. They offer non-invasive sensing technologies to identify the composition of primary and secondary materials without time- and cost-consuming sample preparation and chemical analyses. Based on material-specific physical properties, such sensors provide huge advantages for a selected material group, but show limitations, when it comes to materials beyond that group, as well as for complex and/or unknown, variable material streams. 

To innovate available technology, overcome limitations of individual sensors and expand the range of detectable materials, we focus on (1) the development of new, tailored sensor solutions and on (2) the integration of sensors into smart and agile networks. In particular, we combine reflectance hyperspectral imaging (HSI) sensors from VNIR to LWIR with emission spectroscopy using laser-induced fluorescence (LiF) to map material types and their abundances. We investigate further integration concepts for refining position information in 3D (RGB, laser profiler) for improved signal acquisition. We evaluate concepts on how resulting data can enable efficient control mechanisms and provide the guidance of subsequent sensors in automated analysis cycles for validation and updating mapping results. Developed concepts then allow to expand the toolkit of sensors (e.g. by Raman, XRF or LIBS) within the network according to the scope of individual research questions and application cases.
 

RESEARCH FOCUS

 

The HELIOS lab is a research infrastructure to explore the potentials and limits of optical sensors for raw material identification. The concept of HELIOS represents a combination of the EYES with the BRAIN. The EYES are our sensors to record selected physical parameters and the BRAIN provides an efficient and learning data processing architecture. Developments provide technical concepts for operational conditions and workflows for real-time data processing as a basis for process control and monitoring.

 

sensor development and integration for innovative concepts in material stream characterisation and digitalisation in real-time

 

  • Laser-induced fluorescence (LiF) line-can sensor integrated with HSI sensor, prototype (inSPECTor project) for drill cores

  • Raman sensor for point validation integrated within HSI and LiF sensor network, prototype (RAMSES-4-CE project)

in-line, spectroscopy-based sensor networks for hyperspectral reflectance (HSI), laser-induced fluorescence (LiF), Raman, x-ray fluorescence (XRF) and laser-induced breakdown spectroscopy (LIBS)

  • infrastructure for battery recycling (XRF, LIBS, robots, conveyor, GPU, InfraDatRec project)

  • high-performance computing (GPU, CirculAIre)

primary raw materials: esp. critical raw materials in drill cores and re-mining material: 

 

  • rare-earth elements (REE) (inSPECTor project, RAMSES-4-CE project)

secondary raw materials: esp. complex, variable waste streams including valuable as well as contaminating components. Solutions explore material- and object-based approaches to meet the current and future challenges in recycling:

  • automated material detection in e-waste recycling (RAMSES-4-CE project)

  • automated material detection in battery recycling (DIGISORT project)

  • automated material detection in electrolyser recycling (AI4H2/ ReNaRe/H2Giga)

  • automated material detection in automotive recycling (Car2Car project)

  • automated detection of additives in polymer recycling (FINEST project)

RESEARCH PROJECTS

inSPECtor: 

EIT RawMaterials upscaling project (2017 - 2020)

development of an integrated reflectance and laser-induced fluorescence sensor system for REE mapping in drill cores

partners: HZDR-HIF, TU Bergakademie Freiberg, Geological Survey of Finland 

(GTK), Freiberg Instruments GmbH, Spectral Imaging Ltd. (SPECIM) 

 

link: https://eitrawmaterials.eu/project/inspector/

publications:

     IEEEsensors 2019: https://ieeexplore.ieee.org/document/8956697

     Sensors 2019: https://www.mdpi.com/1424-8220/19/10/2219

     PhysChemChemPhys 2019: https://pubmed.ncbi.nlm.nih.gov/31309210/

data:

     REE spectral library LIF: 

          https://essd.copernicus.org/articles/13/4465/2021/          (paper)

          https://zenodo.org/records/4054606          (data)

InfraDatRec: 

BMBF infrastructure - setup of Data Mining Lab Freiberg (2021 - 2023)

improvement of data availability in the field of battery materials and technologies

partners: HZDR-HIF, TU Bergakademie Freiberg IAP, ITC  and MVTAT, Fraunhofer 

IKTS and IISB

 

links: https://www.linkedin.com/posts/datamininglabfreiberg_infradatrec-datamininglab-dmlf-activity-7089618218218049536-4nJP/

DataMiningLabFreiberg: https://dmlf.de/


 

DIGISORT: 

BMBF cluster project - recycling / green batteries (2021 - 2023)

development an optical sensor system for the rapid characterisation of battery 

components

digitalisation of material stream for subsequent recycling processing decisions

partners: HZDR-HIF, TU Bergakademie Freiberg IAPand MVTAT

 

link: https://www.greenbatt-cluster.de/de/projekte/digisort/

 

publications:

     IEEE Whispers 2022: https://ieeexplore.ieee.org/document/9955076

     MDPI Metals 2024: Spectral characterization of battery components from Li-ion battery                                                                          recycling processes. https://www.mdpi.com/2075-4701/14/2/147

RAMSES-4-CE: 

EIT RawMaterials upscaling project (2020 - 2024)

development of Raman spectroscopy integrated with an reflectance and 

laser-induced fluorescence sensor system and combined with advanced machine 

learning for efficient material characterisation of e-waste

partners: HZDR-HIF, TU Bergakademie Freiberg, Geological Survey of Finland 

(GTK), Freiberg Instruments

 

links: https://www.ramses4ce.eu/

 

publications:

     overview: https://www.ramses4ce.eu/publications

data: 

     polymer spectral library: 

          https://rodare.hzdr.de/record/2448

     PCB-Vision - A Multiscene RGB-Hyperspectral Benchmark Dataset of Printed Circuit Boards:

          https://arxiv.org/abs/2401.06528 (paper)

          https://rodare.hzdr.de/record/2704 (dataset)

          https://github.com/hifexplo/PCBVision (codes)

H2GIGA (Subproject ReNaRe-AI4H2): 

BMBF cluster project - sub-project: recycling - sustainable resource use (2021 - 2025)

development of an efficient sensor combination for the rapid characterisation of 

electrolyser cells 

digitalisation of material composition for subsequent recycling processing decisions

partners: KIT, FhG-IPA, HZDR-HIF, RWTH-IME, TU Bergakademie Freiberg 

IKFVW, Nickelhütte Aue, Heraeus Deutschland GmbH&Co KG, OEKO, 

DECHEMA, FZJ 

 

links: https://www.wasserstoff-leitprojekte.de/projects/h2giga

press release: https://manage.wix.com/dashboard/f0a54a12-890c-4109-9e84-1f4c110d9137/blog/overview?referralInfo=sitesdropdown (in German)

publications:

     IEEE IGARSS 2023: https://ieeexplore.ieee.org/document/10282872

     WHIPSPERS 2023: https://ieeexplore.ieee.org/document/10431001

Car2Car:

BMWK funded project - new automotive and system technologies (2023 - 2025)

automated solutions for an robust and real-time identification of car recycling 

products with focus on advanced type discrimination for steel and aluminum in 

complex material mixes using hyperspectral imaging and LIBS-based validation 

methods

partners: BMW AG, Salzgitter Mannesmann Forschung GmbH, Scholz Recycling 

GmbH, Steinert UniSort GmbH, ThyssenKrupp Steel Europe AG, HZDR-HIF, 

TUBAF-MVTAT, TU Munich-FML and IWB and CE, associated Aurubis AG, Novelis 

Deutschland GmbH, Oetinger Aluminium GmbH, Pilkington Automotive 

Deutschland GmbH

 

links:

https://www.hzdr.de/db/Cms?pOid=68877&pNid=0

 

https://www.press.bmwgroup.com/global/article/detail/T0413318EN/from-scrap-to-raw-material:-state-supported-car2car-project-develops-technologies-to-improve-recycling-of-end-of-life-vehicles

FINEST - SP2: Finest Mineral Additives

Core Project in Helmholtz Sustainability Challenge (2022 - 2027)

development of optical sensor solution for mineral additives in polymers of building insolation material (ETICS)

partners: HZDR-HIF, KIT, UFZ, HZB, TUBAF, Uni Greifswald

website: https://finest-project.de/

links: 

https://www.hzdr.de/db/Cms?pOid=66640&pNid=0

https://www.hzdr.de/db/Cms?pOid=67636&pNid=733

https://www.hzdr.de/db/Cms?pOid=70839&pNid=0

RESEARCH INFRASTRUCTURE

The research on multi-sensor systems started with the setup of HELIOS mini (Figure 1, left) in 2018 with sensors for RGB, hyperspectral reflectance (HSI) and laser-induced fluorescence (LiF) covering the visible to near-infrared (VNIR), shortwave infrared (SWIR, and midwave infrared (MWIR) wavelength ranges for signal detection. Activities were expanded by adding robots, a laser profiler, Raman spectroscopy, x-ray fluorescence (XRF) and laser-induced breakdown spectroscopy (LIBS) in the circular HELIOS + setup (Figure 1, right) in 2023.

Additionally, LUNA lab provides capacities for further, in-depth luminescence spectroscopy aiming at method developments for dosimetric and geoscientific applications.

  • HELIOS mini

  • HELIOS +

  • LUNA lab

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