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Detecting Loose Wheel Bolts of a Vehicle Using Accelerometers in the Chassis

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Pattern Recognition and Image Analysis (IbPRIA 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14062))

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Abstract

Increasing road safety has been a society’s goal since the automobile’s invention. One safety aspect that has not been the focus of research so far is that of a loose wheel. Potential accidents could be prevented with the help of early detection of loose wheel bolts. This work investigates how acceleration sensors in the chassis can be used to detect loose wheel bolts. Test drives with tightened and loosened wheel bolts were carried out. Several state-of-the-art semi-supervised anomalous sound detection algorithms are trained on the test drive data. Evaluation and optimization of anomalous sound detection algorithms shows that loose wheel bolts can be reliably detected when at least three out of five wheel bolts are loose. Our study indicates that acoustic preprocessing and careful selection of acoustic features is crucial for performance and more important than the choice of a special algorithm for detecting loose wheel bolts.

Supported by ZF Friedrichshafen AG.

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Authors and Affiliations

  1. Institute of Cognitive Science, University of Osnabrück, Osnabrück, Germany

    Jonas Schmidt & Kai-Uwe Kühnberger

  2. ZF Friedrichshafen AG, Friedrichshafen, Germany

    Jonas Schmidt, Dennis Pape & Tobias Pobandt

Authors
  1. Jonas Schmidt
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  2. Kai-Uwe Kühnberger
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  3. Dennis Pape
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  4. Tobias Pobandt
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Corresponding author

Correspondence to Jonas Schmidt .

Editor information

Editors and Affiliations

  1. University of Alicante, Alicante, Spain

    Antonio Pertusa

  2. University of Alicante, Alicante, Spain

    Antonio Javier Gallego

  3. Universitat Politècnica de València, Valencia, Spain

    Joan Andreu Sánchez

  4. IPO Porto, Coimbra, Portugal

    Inês Domingues

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Schmidt, J., Kühnberger, KU., Pape, D., Pobandt, T. (2023). Detecting Loose Wheel Bolts of a Vehicle Using Accelerometers in the Chassis. In: Pertusa, A., Gallego, A.J., Sánchez, J.A., Domingues, I. (eds) Pattern Recognition and Image Analysis. IbPRIA 2023. Lecture Notes in Computer Science, vol 14062. Springer, Cham. https://doi.org/10.1007/978-3-031-36616-1_53

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  • DOI: https://doi.org/10.1007/978-3-031-36616-1_53

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-36615-4

  • Online ISBN: 978-3-031-36616-1

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