@inproceedings{Fen2022, Author = {Fenja Schwark, Henriette Garmatter, Maria Davila, Lisa Dawel, Alexandra Pehlken, Fabian Cyris, Roland Scharf}, Title = {The application of image recognition methods to improve the performance of waste-to-energy plants}, Year = {2022}, Month = {09}, Booktitle = {EnviroInfo 2022}, type = {inproceedings}, 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.} } @COMMENT{Bibtex file generated on }