Preliminary notesThis research paper presents the approach of automated computerized identification of causal knowledge and causal graphs using monitoring of vibrations and temperatures of sliding bearings of high-power and high-speed process ventilators. Method of Granger causal connectivity analysis of vibration and temperature parameters is presented. This method improves diagnostics of process ventilators because of identification of causal relations and links of vibrations and temperatures in graph form. After computing and plotting causal graphs for vibrations and temperatures, causal density is computed as a measure of dynamical complexity of system. Numerical values of causal density are taken as indicators of systems "health" of process ventilators.
Key words: causal density; causal graph; Granger causal analysis; process ventilators; sliding bearings
Automatska identifikacija uzročnog znanja i uzročnih grafova u tehničkim sustavima procesnih ventilatoraPrethodno priopćenje U ovom radu je dan pristup automatskog računarskog identificiranja uzročnog znanja i uzročnih grafova putem monitoringa vibracija i temperatura postrojenja procesnih ventilatora velikih snaga i velikih brzina vrtnje. Predstavljena je metoda Granger-ove uzročne analize uzročnih veza mjernih parametara vibracija i temperature. Ova metoda poboljšava dijagnostiku procesnih ventilatora zbog identifikacije uzročnih zakonitosti parametara vibracija i temperatura u dijagramskom obliku. Nakon računanja i crtanja uzročnog grafa za vibracije i temperature, računa se uzročna gustoća, kao mjera dinamičke složenosti sustava. Numeričke vrijednosti uzročne gustoće se uzimaju kao indikatori sustavnog "zdravlja" procesnih ventilatora.
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