Decision tree based qualitative analysis of operating regimes in industrial production processes

Tamás Varga, Ferenc Szeifert, József Réti, János Abonyi

Research output: Chapter in Book/Report/Conference proceedingChapter

1 Citation (Scopus)

Abstract

The qualitative analysis of comp lex process systems is an im portant task at the design of control and process monitoring algorithm s. Qualitative models require interpretable description of the operating regimes of the process. This work shows a novel approach to discover and isolate operating regimes of process systems based on process models, time series analysis, and decision tree induction technique. The novelty of this approach is the application of time series segmentat ion algorithms to detect the homogeneous periods of the operation. Advanced sequence alignment algorithm used in bioinformatics is applied for the calculation of the similarity of the process trends described by qualitative variables. Decision tree induction is applied for the transformation of this hidden knowledge into easily in terpretable rule base to represent the operation regions of the process. The whole methodology is applied to detect operating regimes of an industrial fixed bed tube reactor.

Original languageEnglish
Title of host publication18th European Symposium on Computer Aided Process Engineering
EditorsBertrand Braunschweig, Xavier Joulia
Pages1039-1044
Number of pages6
DOIs
Publication statusPublished - Oct 3 2008

Publication series

NameComputer Aided Chemical Engineering
Volume25
ISSN (Print)1570-7946

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Keywords

  • decision tree
  • operating regime
  • qualitative analysis
  • sequence alignment

ASJC Scopus subject areas

  • Chemical Engineering(all)
  • Computer Science Applications

Cite this

Varga, T., Szeifert, F., Réti, J., & Abonyi, J. (2008). Decision tree based qualitative analysis of operating regimes in industrial production processes. In B. Braunschweig, & X. Joulia (Eds.), 18th European Symposium on Computer Aided Process Engineering (pp. 1039-1044). (Computer Aided Chemical Engineering; Vol. 25). https://doi.org/10.1016/S1570-7946(08)80179-4