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A Study of OBF-ARMAX Performance for Modelling of a Mechanical System Excited by a Low Frequency Signal for Condition Monitoring
University of Gävle, Faculty of Engineering and Sustainable Development, Department of Electrical Engineering, Mathematics and Science, Electronics.ORCID iD: 0000-0003-2162-6996
University of Gävle, Faculty of Engineering and Sustainable Development, Department of Electrical Engineering, Mathematics and Science, Electronics.ORCID iD: 0000-0003-2887-049x
2023 (English)In: Recent Developments in Model-Based and Data-Driven Methods for Advanced Control and Diagnosis / [ed] Janusz Kacprzyk, Springer , 2023, p. 73-82Chapter in book (Refereed)
Abstract [en]

A digital twin of a mechanical system (a pair of axial rolls in a ring mill used in a steel plant) with poles close to the unit circle and the real axis in the discrete pole-zero map was built. The system was excited by a signal concentrated in the low-frequency band. For this particular case, it is shown that the ad-hoc combination of ARMAX and orthonormal basis filter model structures outperform model structures based on either ARMAX or orthonormal basis functions when estimating the poles of the basis by analyzing the data in the frequency domain. The followed modelling methodology of the system is described in detail to help replicate the work for similar systems in the steel industry. Real production data from a steel plant were used in contrast to previous studies, where the combination of ARX and ARMAX with orthonormal basis filter model structures was evaluated using simulated data instead of real data. We believe that the resultant model can be used when having systems with poles close to the unit circle and real axis and poor excited input signal concentrated in the low frequency band. The resultant model can be used for condition monitoring and failure detection.

Place, publisher, year, edition, pages
Springer , 2023. p. 73-82
Series
Studies in Systems, Decision and Control (SSDC), ISSN 2198-4182, E-ISSN 2198-4190 ; 467
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:hig:diva-42666DOI: 10.1007/978-3-031-27540-1_7Scopus ID: 2-s2.0-85162239790ISBN: 978-3-031-27540-1 (electronic)ISBN: 978-3-031-27539-5 (print)OAI: oai:DiVA.org:hig-42666DiVA, id: diva2:1778611
Available from: 2023-07-03 Created: 2023-07-03 Last updated: 2024-05-21Bibliographically approved

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Bautista Gonzalez, OscarRönnow, Daniel

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CiteExportLink to record
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Citation style
  • apa
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