MODEL SELECTION IN LARGE-SCALE DATABASES

A procedure for surveying process data sets is presented. For this, linear models constructed in varying length, sliding data windows to determine the usefulness of data segments for process identification are utilised. The discussed approach has been applied to an industrial wood debarking plant and a biomass boiler analysis, enabling the preliminary study of process variables and conditions affecting the non-optimal process conditions. In addition, main process interactions and delays were easily discovered from the structures of the interpretable linear model candidates. It is concluded that the analysis can provide valuable information also for modelling and control of continuous processes.