Preliminary communication

https://doi.org/10.17559/TV-20140312135635

Automatic identification of causal knowledge and causal graphs in technical systems of process ventilators

Senad Alić ; University of Zenica, Polytechnical Faculty, Fakultetska 1, 72000 Zenica, Bosnia and Herzegovina
Sabahudin Jašarević orcid.org/0000-0002-0692-1121 ; University of Zenica, Faculty of Mechanical Engineering, Fakultetska 1, 72000 Zenica, Bosnia and Herzegovina
Safet Brdarević ; University of Zenica, Faculty of Mechanical Engineering, Fakultetska 1, 72000 Zenica, Bosnia and Herzegovina
Mustafa Imamović ; Arcelor Mittal Zenica, Bosnia and Herzegovina
Indir Jaganjac ; Arcelor Mittal Zenica, Bosnia and Herzegovina

Abstract

This 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.

Keywords

causal density; causal graph; Granger causal analysis; process ventilators; sliding bearings

Hrčak ID:

156852

URI

https://hrcak.srce.hr/156852

Publication date:

27.4.2016.

Article data in other languages: croatian

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