Digitalisation of Refuse Sorting with Image Recognition and Time Series Analysis

The recycling of municipal solid refuse is a major challenge on the way towards a circular economy. Although solid refuse generation is increasing in the EU, the recycling rates are still below 50% on average (Neligan 2018). Hence, innovative technologies are required to increase recycling rates and cope with the predicted amount of municipal solid refuse. The KI-Waste project researches new technologies and optimisations to increase the sorting quality and yield of municipal solid refuse, thus providing solutions to increase the recycling rates. The vision of KI-Waste is to determine the compositions of the refuse streams in a sorting facility and combine this information with telemetry data from the sorting machines.

Refuse separation and sorting is currently done by recycling plants that are manually optimised for a fixed refuse composition. Since the refuse compositions constantly change, these plants deliver either suboptimal sorting performances or require constant monitoring and adjustments by the plant operators. Image recognition offers the possibility to continuously monitor the refuse composition on the conveyor belts in a sorting facility. When information about the refuse composition is combined with parameters and measurements of the sorting machinery, the sorting performance of a plant can be continuously monitored, problems detected, optimisations suggested and trends predicted. This article describes solutions for multispectral and 3D image capturing of refuse streams and evaluates the performance of image segmentation models. The image segmentation models are trained with synthetic training data to reduce the manual labelling effort thus reducing the costs of the image recognition introduction. Furthermore, an outlook on the combination of image recognition data with parameters and measurements of the sorting machinery in a combined time series analysis is provided.



Copyright: © Lehrstuhl für Abfallverwertungstechnik und Abfallwirtschaft der Montanuniversität Leoben
Quelle: Recy & Depotech 2022 (November 2022)
Seiten: 6
Preis: € 3,00
Autor: Heimo Gursch
S. Körner
Franz Thaler
Dipl.-Ing. BSc Georg Waltner
DI Alfred Rinnhofer
 
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