Multivariate soft sensor for product monitoring in the debutanizer column with deep learning

  • Imron Rosyadi Jenderal Soedirman University
  • Arief Wisnu Wardhana
  • Muhammad Syaiful Aliim Universitas Jenderal Soedirman
  • Rifah Ediati Universitas Jenderal Soedirman
  • D Ristiawan

Abstract

Soft sensors have been proposed extensively for predicting ill-to-measure variables in industrial processes. In this study, we developed a multivariate soft sensor for debutanizer columns. A soft sensor was proposed to replace the chromatograph-based butane content from the debutanizer column. Recently, deep learning methods have been implemented for better feature representation of complex systems. We developed an LSTM-based multivariate soft sensor that can better represent the dynamics of a debutanizer column system. Our results show that the univariate LSTM soft sensor performs better than previously proposed methods.

Published
2023-01-31
How to Cite
ROSYADI, Imron et al. Multivariate soft sensor for product monitoring in the debutanizer column with deep learning. Proceeding ICMA-SURE, [S.l.], p. 9-17, jan. 2023. ISSN 2808-2702. Available at: <https://jos.unsoed.ac.id/index.php/eprocicma/article/view/7762>. Date accessed: 02 apr. 2025. doi: https://doi.org/10.20884/2.procicma.2023.2.1.7762.