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Vibration Monitoring of Winch Epicyclic Gearboxes Using Cyclostationarity and Autoregressive Signal Model

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Advances in Condition Monitoring of Machinery in Non-Stationary Operations

Part of the book series: Lecture Notes in Mechanical Engineering ((LNME))

Abstract

This paper proposes a model-based technique using a combination of cyclostationary and autoregressive signal modelling in order to detect wear in a multistage planetary gear of lifting cranes. The first-order cyclostationarity is exploited by the analysis of the Time Synchronous Average part (TSA) of the angular resampled vibration signal. Then an autoregressive model (AR) is applied to the TSA part in order to extract a residual signal containing pertinent fault signatures. The paper also explores the efficiency of a number of methods commonly used in vibration monitoring. Condition monitoring indicators are then extracted from different treated signals. In the experimental part, all these techniques are applied to a test bench data of a lifting winch. The goal is to trend the evolution of the extracted features during the test. This study reveals that the proposed procedure using this combination enhances the ability to detect and diagnose mechanical wear of winch planetary gears.

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Acknowledgments

The authors wish to thank the CETIM and specially the MLS committee for its technical and financial support.

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Authors and Affiliations

  1. Centre Technique des Industries Mécaniques, CETIM, 52 av Félix Louat, BP, 80067, 60304, Senlis Cedex, France

    Bassel Assaad & Mario Eltabach

Authors
  1. Bassel Assaad
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  2. Mario Eltabach
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Corresponding author

Correspondence to Mario Eltabach .

Editor information

Editors and Affiliations

  1. Engineering Department, University of Ferrara, Ferrara, Italy

    Giorgio Dalpiaz

  2. Department of Science and Engineering Methods, University of Modena and Reggio Emilia, Reggio Emilia, Italy

    Riccardo Rubini

  3. Engineering Department, University of Ferrara, Ferrara, Italy

    Gianluca D'Elia

  4. Department of Science and Engineering Methods, University of Modena and Reggio Emilia, Reggio Emilia, Italy

    Marco Cocconcelli

  5. Mechanical Engineering Department, National School of Engineers of Sfax, Sfax, Tunisia

    Fakher Chaari

  6. Institute of Mining Engineering, Diagnostics and Vibro-Acoustics Science Laboratory, Wrocław University of Technology, Wrocław, Poland

    Radoslaw Zimroz

  7. Institute of Mining Engineering, Diagnostics and Vibro-Acoustics Science Laboratory, Wrocław University of Technology, Wrocław, Poland

    Walter Bartelmus

  8. Mechanical Engineering Department, National School of Engineers of Sfax, Sfax, Tunisia

    Mohamed Haddar

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Assaad, B., Eltabach, M. (2014). Vibration Monitoring of Winch Epicyclic Gearboxes Using Cyclostationarity and Autoregressive Signal Model. In: Dalpiaz, G., et al. Advances in Condition Monitoring of Machinery in Non-Stationary Operations. Lecture Notes in Mechanical Engineering. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39348-8_22

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  • DOI: https://doi.org/10.1007/978-3-642-39348-8_22

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-39347-1

  • Online ISBN: 978-3-642-39348-8

  • eBook Packages: EngineeringEngineering (R0)

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