Abstract
Machine Learning ML algorithms can be combined with the modular
automation protocol MTP and recognize the flooding behavior of
laboratory fluids separation columns. Hence, artificial intelligence AI
tools with deep learning DL offer a high potential for the process
industry and allow to capture operating states that are otherwise
difficult to detect or model. However, the advanced methods are only
hesitantly applied in practice. This article provides an overview on how
artificial intelligence-based algorithms can be implemented in existing
laboratory plants. Process sensor data as well as image data are used to
model the flooding behavior of distillation and extraction columns and
the system is adapted to the existing modular automation standard of the
Module Type Package MTP.
Topical Heading
Separations: Materials, Devices and Processes
Keywords Clustering, Convolutional neural networks, Flooding, Process
monitoring, Time series forecasting
1Department of Biochemical and Chemical Engineering,
Laboratory of Equipment Design, TU Dortmund University,
Emil-Figge-Strasse 68, Dortmund, 44227, Germany
All authors contributed equally