The qualitative analysis of complex process systems is an important task at the designof control and process monitoring algorithms. Qualitative models require interpretabledescription of the operating regimes of the process. This work shows a novel approachto discover and isolate operating regimes of process systems based on process models,time series analysis, and decision tree induction technique. The novelty of this approachis the application of time series segmentation algorithms to detect the homogeneousperiods of the operation. Advanced sequence alignment algorithm used inbioinformatics is applied for the calculation of the similarity of the process trendsdescribed by qualitative variables. Decision tree induction is applied for thetransformation of this hidden knowledge into easily interpretable rule base to representthe operation regions of the process. The whole methodology is applied to detectoperating regimes of an industrial fixed bed tube reactor.
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