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Title: Data alignment via dynamic time warping as a prerequisite for batch-end quality prediction
Authors: Gins, Geert ×
Espinosa, Jairo
Smets, Ilse
Van Brempt, Wim
Van Impe, Jan #
Issue Date: 2006
Publisher: Springer
Series Title: Lecture Notes in Computer Science vol:4065 pages:506-510
Conference: Industrial Conference on Data Mining ICDM'2006 edition:6 location:Leipzig (Germany) date:July 14-15, 2006
Abstract: In this work, a 4-phase dynamic time warping is implemented to align measurement profiles from an existing chemical batch reactor process, making all batch measurement profiles equal in length, while also matching the major events occurring during each batch run. This data alignment is the first step towards constructing an inferential batch-end quality sensor, capable of predicting 3 quality variables before batch run completion using a multivariate statistical partial least squares model. This inferential sensor provides on-line quality predictions, allowing corrective actions to be performed when the quality of the polymerization product does not meet the specifications, saving valuable production time and reducing operation cost.
Description: [**]
ISSN: 0302-9743
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Bio- & Chemical Systems Technology, Reactor Engineering and Safety Section
× corresponding author
# (joint) last author

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