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

verfasst von

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

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.

Organisationseinheit(en)

Institut für Kraftwerkstechnik und Wärmeübertragung

Externe Organisation(en)

OFFIS - Institut für Informatik
EEW Energy from Waste GmbH

Typ

Aufsatz in Konferenzband

Seiten

167-176

Anzahl der Seiten

10

Publikationsdatum

2022

Publikationsstatus

Veröffentlicht

Peer-reviewed

Ja

ASJC Scopus Sachgebiete

Angewandte Informatik

Ziele für nachhaltige Entwicklung

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

Elektronische Version(en)

https://dl.gi.de/bitstream/handle/20.500.12116/39413/EnviroInfo2022_ShortPaper_26.pdf?sequence=1&isAllowed=y (Zugang: Offen)