Bauer, ChristineChristineBauerWagner, RebeccaRebeccaWagnerLeisner, JohannesJohannesLeisner2022-11-302022-11-302022-09https://publica.fraunhofer.de/handle/publica/429417In the context of circular economy, waste wood is an important resource. However, according to the German waste wood ordinance, sorting into four categories is necessary before recycling. These categories describe the purity of waste wood based on possible contamination, like paint, foreign bodies, or wood preservatives. Only the purest two categories are allowed to be recycled. For categorization, manual sorting is currently used. This is not only time-consuming and expensive, but also relatively inaccurate. An automated, sensor-based solution would lead to cost savings for recycling companies and also support a sustainable use of resources. For this purpose, a non-contact measuring system, which can examine waste wood chips, will be developed within the project AHOY. As a proof of concept, this paper presents dual energy X-ray transmission (DEXRT) for the discrimination between clean wood and the most common contaminants polyvinyl chloride and white lead paint. The results show that even thin layers of contaminants can be detected. The DE-XRT data are intended for a later fusion with near-infrared spectroscopy, which is sensitive to organic contaminants hard to detect by DE-XRT. Artificial neural networks will be applied to the fused data to achieve a sorting process that yields waste wood chips of the purest two categories.enconference paper