The application of image recognition methods to improve the performance of waste-to-energy plants

Fenja Schwark; Henriette Garmatter; Maria Davila; Lisa Dawel; Alexandra Pehlken; Fabian Cyris; Roland Scharf

The application of image recognition methods to improve the performance of waste-to-energy plants

Fenja Schwark, Henriette Garmatter, Maria Davila, Lisa Dawel, Alexandra Pehlken, Fabian Cyris, Roland Scharf

Institut für Kraftwerkstechnik und Wärmeübertragung

Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review

Abstract

In this paper, we present an image recognition method to improve the performance of waste-to-energy plants. Thermal treatment of waste in waste-to-energy plants is central for the treatment of municipal solid waste. The heterogeneous nature of municipal solid waste results in a fluctuating lower calorific value to which plant operation must be adapted. Compensating for drastic changes in the lower calorific value is challenging for plant operation and can require short-term interventions. Estimating the lower calorific value prior to the combustion process should reduce the number of short-term interventions. In this work, we propose a process-engineering approach to estimate the lower calorific value of waste as a new application of image recognition in waste-to-energy plants. The method is implemented using videos and sensor data from a case study in a real waste-to-energy plant in Germany.

Originalsprache	Englisch
Titel des Sammelwerks	EnviroInfo 2022 - Short-/Work in Progress-Papers
Herausgeber/-innen	Volker Wohlgemuth, Stefan Naumann, Hans-Knud Arndt, Grit Behrens, Maximilian Hob
Herausgeber (Verlag)	Gesellschaft fur Informatik (GI)
Seiten	167-176
Seitenumfang	10
ISBN (elektronisch)	9783885797227
Publikationsstatus	Veröffentlicht - 2022
Veranstaltung	36th International Conference on Informatics for Environmental Protection: Environmental Information and Communication Technologies, EnviroInfo 2022 - Hamburg, Deutschland Dauer: 26 Sept. 2022 → 28 Sept. 2022

Publikationsreihe

Name	Lecture Notes in Informatics (LNI), Proceedings - Series of the Gesellschaft fur Informatik (GI)
Band	P-328
ISSN (Print)	1617-5468
ISSN (elektronisch)	2944-7682

Konferenz

Konferenz	36th International Conference on Informatics for Environmental Protection: Environmental Information and Communication Technologies, EnviroInfo 2022
Land/Gebiet	Deutschland
Ort	Hamburg
Zeitraum	26 Sept. 2022 → 28 Sept. 2022

UN-Ziele für nachhaltige Entwicklung (SDGs)

2015 einigten sich die UN-Mitgliedstaaten auf 17 globale Ziele für nachhaltige Entwicklung (Sustainable Development Goals, SDGs) zur Beendigung von Armut, zum Schutz des Planeten und zur Förderung des allgemeinen Wohlstands. Hiermit leisten wir einen Beitrag zu folgendem/n Ziel(en) für nachhaltige Entwicklung (SDGs):

SDG 11 Nachhaltige Städte und Gemeinschaften
SDG 12 Verantwortungsvoller Konsum und Produktion

ASJC Scopus Sachgebiete

Angewandte Informatik

Zugriff auf Dokument

https://dl.gi.de/bitstream/handle/20.500.12116/39413/EnviroInfo2022_ShortPaper_26.pdf?sequence=1&isAllowed=yLizenz: Sonstige

Andere Dateien und Links

Verknüpfung zur Publikation in Scopus

Dieses zitieren

Schwark, F., Garmatter, H., Davila, M., Dawel, L., Pehlken, A., Cyris, F., & Scharf, R. (2022). The application of image recognition methods to improve the performance of waste-to-energy plants. in V. Wohlgemuth, S. Naumann, H.-K. Arndt, G. Behrens, & M. Hob (Hrsg.), EnviroInfo 2022 - Short-/Work in Progress-Papers (S. 167-176). (Lecture Notes in Informatics (LNI), Proceedings - Series of the Gesellschaft fur Informatik (GI); Band P-328). Gesellschaft fur Informatik (GI). https://dl.gi.de/bitstream/handle/20.500.12116/39413/EnviroInfo2022_ShortPaper_26.pdf?sequence=1&isAllowed=y

Schwark, Fenja ; Garmatter, Henriette ; Davila, Maria et al. / The application of image recognition methods to improve the performance of waste-to-energy plants. EnviroInfo 2022 - Short-/Work in Progress-Papers. Hrsg. / Volker Wohlgemuth ; Stefan Naumann ; Hans-Knud Arndt ; Grit Behrens ; Maximilian Hob. Gesellschaft fur Informatik (GI), 2022. S. 167-176 (Lecture Notes in Informatics (LNI), Proceedings - Series of the Gesellschaft fur Informatik (GI)).

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title = "The application of image recognition methods to improve the performance of waste-to-energy plants",

abstract = "In this paper, we present an image recognition method to improve the performance of waste-to-energy plants. Thermal treatment of waste in waste-to-energy plants is central for the treatment of municipal solid waste. The heterogeneous nature of municipal solid waste results in a fluctuating lower calorific value to which plant operation must be adapted. Compensating for drastic changes in the lower calorific value is challenging for plant operation and can require short-term interventions. Estimating the lower calorific value prior to the combustion process should reduce the number of short-term interventions. In this work, we propose a process-engineering approach to estimate the lower calorific value of waste as a new application of image recognition in waste-to-energy plants. The method is implemented using videos and sensor data from a case study in a real waste-to-energy plant in Germany.",

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author = "Fenja Schwark and Henriette Garmatter and Maria Davila and Lisa Dawel and Alexandra Pehlken and Fabian Cyris and Roland Scharf",

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Schwark, F, Garmatter, H, Davila, M, Dawel, L, Pehlken, A, Cyris, F & Scharf, R 2022, The application of image recognition methods to improve the performance of waste-to-energy plants. in V Wohlgemuth, S Naumann, H-K Arndt, G Behrens & M Hob (Hrsg.), EnviroInfo 2022 - Short-/Work in Progress-Papers. Lecture Notes in Informatics (LNI), Proceedings - Series of the Gesellschaft fur Informatik (GI), Bd. P-328, Gesellschaft fur Informatik (GI), S. 167-176, 36th International Conference on Informatics for Environmental Protection: Environmental Information and Communication Technologies, EnviroInfo 2022, Hamburg, Deutschland, 26 Sept. 2022. <https://dl.gi.de/bitstream/handle/20.500.12116/39413/EnviroInfo2022_ShortPaper_26.pdf?sequence=1&isAllowed=y>

The application of image recognition methods to improve the performance of waste-to-energy plants. / Schwark, Fenja; Garmatter, Henriette; Davila, Maria et al.
EnviroInfo 2022 - Short-/Work in Progress-Papers. Hrsg. / Volker Wohlgemuth; Stefan Naumann; Hans-Knud Arndt; Grit Behrens; Maximilian Hob. Gesellschaft fur Informatik (GI), 2022. S. 167-176 (Lecture Notes in Informatics (LNI), Proceedings - Series of the Gesellschaft fur Informatik (GI); Band P-328).

Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review

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AU - Garmatter, Henriette

AU - Davila, Maria

AU - Dawel, Lisa

AU - Pehlken, Alexandra

AU - Cyris, Fabian

AU - Scharf, Roland

N1 - Funding Information: This work is supported by the Federal Ministry for Economic Affairs and Climate Action on the basis of a decision by the German Bundestag (FKZ 03EE5038).

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N2 - In this paper, we present an image recognition method to improve the performance of waste-to-energy plants. Thermal treatment of waste in waste-to-energy plants is central for the treatment of municipal solid waste. The heterogeneous nature of municipal solid waste results in a fluctuating lower calorific value to which plant operation must be adapted. Compensating for drastic changes in the lower calorific value is challenging for plant operation and can require short-term interventions. Estimating the lower calorific value prior to the combustion process should reduce the number of short-term interventions. In this work, we propose a process-engineering approach to estimate the lower calorific value of waste as a new application of image recognition in waste-to-energy plants. The method is implemented using videos and sensor data from a case study in a real waste-to-energy plant in Germany.

AB - In this paper, we present an image recognition method to improve the performance of waste-to-energy plants. Thermal treatment of waste in waste-to-energy plants is central for the treatment of municipal solid waste. The heterogeneous nature of municipal solid waste results in a fluctuating lower calorific value to which plant operation must be adapted. Compensating for drastic changes in the lower calorific value is challenging for plant operation and can require short-term interventions. Estimating the lower calorific value prior to the combustion process should reduce the number of short-term interventions. In this work, we propose a process-engineering approach to estimate the lower calorific value of waste as a new application of image recognition in waste-to-energy plants. The method is implemented using videos and sensor data from a case study in a real waste-to-energy plant in Germany.

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KW - process modeling

KW - waste properties

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T3 - Lecture Notes in Informatics (LNI), Proceedings - Series of the Gesellschaft fur Informatik (GI)

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BT - EnviroInfo 2022 - Short-/Work in Progress-Papers

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A2 - Naumann, Stefan

A2 - Arndt, Hans-Knud

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A2 - Hob, Maximilian

PB - Gesellschaft fur Informatik (GI)

T2 - 36th International Conference on Informatics for Environmental Protection: Environmental Information and Communication Technologies, EnviroInfo 2022

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Schwark F, Garmatter H, Davila M, Dawel L, Pehlken A, Cyris F et al. The application of image recognition methods to improve the performance of waste-to-energy plants. in Wohlgemuth V, Naumann S, Arndt HK, Behrens G, Hob M, Hrsg., EnviroInfo 2022 - Short-/Work in Progress-Papers. Gesellschaft fur Informatik (GI). 2022. S. 167-176. (Lecture Notes in Informatics (LNI), Proceedings - Series of the Gesellschaft fur Informatik (GI)).