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Towards Data Driven Dynamical System Discovery for Condition Monitoring a Reciprocating Compressor Example

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  • First Online:
Proceedings of IncoME-VI and TEPEN 2021

Part of the book series: Mechanisms and Machine Science ((Mechan. Machine Science,volume 117))

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Abstract

A viable data driven approach for determining dynamical systems describing engineering processes would be a valuable tool in condition monitoring. The application of the SINDy algorithm for dynamical system discovery is investigated in the context of a reciprocating compressor. A feasibility study was carried out in which an attempt was made to recover a model of the compressor from synthetic data obtained from that model. A simplified model of the compressor with two degrees of freedom was developed from an existing model. Following the SINDy approach a parsimonious model was constructed from a large library of functions using sparse regression. This model has the same structure as and similar coefficients to the original model thus demonstrating the potential of this approach.

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References

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Author information

Authors and Affiliations

  1. Centre for Efficiency and Performance Engineering, University of Huddersfield, Huddersfield, HD1 3DH, UK

    Ann Smith

  2. Centre for Mathematics and Data Science, University of Huddersfield, Huddersfield, HD1 3DH, UK

    Ann Smith & W. T. Lee

  3. MACSI, Department of Mathematics and Statistics, University of Limerick, Limerick, Ireland

    W. T. Lee

Authors
  1. Ann Smith
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  2. W. T. Lee
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Corresponding author

Correspondence to Ann Smith .

Editor information

Editors and Affiliations

  1. School of Mechanical Engineering, Hebei University of Technology, Tianjin, China

    Hao Zhang

  2. School of Mechanical Engineering, Hebei University of Technology, Tianjin, China

    Guojin Feng

  3. School of Mechanical and Electrical Engineering, Beijing Information Science and Technology University, Beijing, China

    Hongjun Wang

  4. University of Huddersfield, Huddersfield, UK

    Fengshou Gu

  5. University of Manchester, Manchester, UK

    Jyoti K. Sinha

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© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

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Smith, A., Lee, W.T. (2023). Towards Data Driven Dynamical System Discovery for Condition Monitoring a Reciprocating Compressor Example. In: Zhang, H., Feng, G., Wang, H., Gu, F., Sinha, J.K. (eds) Proceedings of IncoME-VI and TEPEN 2021. Mechanisms and Machine Science, vol 117. Springer, Cham. https://doi.org/10.1007/978-3-030-99075-6_17

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  • DOI: https://doi.org/10.1007/978-3-030-99075-6_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-99074-9

  • Online ISBN: 978-3-030-99075-6

  • eBook Packages: EngineeringEngineering (R0)

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