“Online Identification of a Mechanical System in the Frequency Domain with Short-Time DFT”

Authors: Niko Nevaranta, Jukka Parkkinen, Tuomo Lindh, Markku Niemelä, Olli Pyrhönen and Juha Pyrhönen,
Affiliation: Lappeenranta University of Technology
Reference: 2015, Vol 36, No 3, pp. 157-165.

Keywords: Kalman filter, Nonparametric estimation, Online identification, Short-time DFT, Two-mass system

Abstract: A proper system identification method is of great importance in the process of acquiring an analytical model that adequately represents the characteristics of the monitored system. While the use of different time-domain online identification techniques has been widely recognized as a powerful approach for system diagnostics, the frequency domain identification techniques have primarily been considered for offline commissioning purposes. This paper addresses issues in the online frequency domain identification of a flexible two-mass mechanical system with varying dynamics, and a particular attention is paid to detect the changes in the system dynamics. An online identification method is presented that is based on a recursive Kalman filter configured to perform like a discrete Fourier transform (DFT) at a selected set of frequencies. The experimental online identification results are compared with the corresponding values obtained from the offline-identified frequency responses. The results show an acceptable agreement and demonstrate the feasibility of the proposed identification method.

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DOI forward links to this article:
[1] Niko Nevaranta, Stijn Derammelaere, Jukka Parkkinen, Bram Vervisch, Tuomo Lindh, Kurt Stockman, Markku Niemela, Olli Pyrhonen and Juha Pyrhonen (2016), doi:10.1109/TIE.2016.2574303
[2] Niko Nevaranta, Stijn Derammelaere, Jukka Parkkinen, Bram Vervisch, Tuomo Lindh, Markku Niemelä and Olli Pyrhönen (2016), doi:10.4173/mic.2016.2.5
[3] N. Nevaranta, M. Goubej, T. Lindh, M. Niemela and O. Pyrhonen (2016), doi:10.1109/EPE.2016.7695535
[4] Mario Aldag and Joachim Horn (2017), doi:10.1109/MMAR.2017.8046817
[5] Mario Aldag and Joachim Horn (2017), doi:10.1109/ASCC.2017.8287356
[6] Mario Aldag and Joachim Horn (2018), doi:10.23919/ECC.2018.8550203
[7] Marek Rehtla, Anna Tupitsina, Tuomo Lindh, Jan-Henri Montonen and Niko Nevaranta (2024), doi:10.1109/ECCEEurope62508.2024.10752087
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BibTeX:
@article{MIC-2015-3-3,
  title={{Online Identification of a Mechanical System in the Frequency Domain with Short-Time DFT}},
  author={Nevaranta, Niko and Parkkinen, Jukka and Lindh, Tuomo and Niemelä, Markku and Pyrhönen, Olli and Pyrhönen, Juha},
  journal={Modeling, Identification and Control},
  volume={36},
  number={3},
  pages={157--165},
  year={2015},
  doi={10.4173/mic.2015.3.3},
  publisher={Norwegian Society of Automatic Control}
};