Logo des Repositoriums
 

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

Kurzanzeige
dc.contributor.authorSchwark, Fenja
dc.contributor.authorGarmatter, Henriette
dc.contributor.authorDavila, Maria
dc.contributor.authorDawel, Lisa
dc.contributor.authorPehlken, Alexandra
dc.contributor.authorCyris, Fabian
dc.contributor.authorScharf, Roland
dc.contributor.editorWohlgemuth, Volker
dc.contributor.editorNaumann, Stefan
dc.contributor.editorArndt, Hans-Knud
dc.contributor.editorBehrens, Grit
dc.contributor.editorHöb, Maximilian
dc.date.accessioned2022-09-19T09:20:54Z
dc.date.available2022-09-19T09:20:54Z
dc.date.issued2022
dc.description.abstractIn 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.en
dc.identifier.isbn978-3-88579-722-7
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/39413
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofEnviroInfo 2022
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-328
dc.subjectwaste-to-energy
dc.subjectimage recognition
dc.subjectwaste properties
dc.subjectprocess modeling
dc.titleThe application of image recognition methods to improve the performance of waste-to-energy plantsplantsen
dc.typeText/Conference Paper
gi.citation.publisherPlaceBonn
gi.citation.startPage167
gi.conference.date26.-30- September 2022
gi.conference.locationHamburg

Dateien

Originalbündel
1 - 1 von 1
Vorschaubild
Name:
EnviroInfo2022_ShortPaper_26.pdf
Größe:
611.65 KB
Format:
Adobe Portable Document Format
Herunterladen

Sammlungen

P328 - EnviroInfo 2022
Environmental Informatics 2022