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Parallel Autoregressive Modeling as a Tool for Diagnosing Localized Gear Tooth Faults

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Book cover Advances in Condition Monitoring of Machinery in Non-Stationary Operations

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

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Abstract

One of the standard approaches widely used in the field of localized gear tooth fault diagnosis is the creation of residual signals i.e. signals obtained after removing the deterministic frequency components from a Time Synchronously Averaged vibration signals. Most of the time these components are removed based on the knowledge of the characteristic gearbox frequencies. Sometimes however such information is not available. AR modeling, a type of time series modeling, has been found to be capable of faithfully estimating the deterministic content of the signal allowing meaningful residual signals to be created. An improvement to the classic AR modeling approach is proposed in this text. The method is applied to experimental data taken from a gearbox in both healthy and faulty condition. The improvement derived from the new method is quantified through a comparison with results obtained by applying Time Synchronous Averaging and the classic AR modeling method to the experimental data.

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Authors and Affiliations

  1. ABB Corporate Research Center, Ul. Starowiślna 13A, 31-038, Kraków, Poland

    Paweł Rzeszuciński & James R. Ottewill

Authors
  1. Paweł Rzeszuciński
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  2. James R. Ottewill
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Corresponding author

Correspondence to Paweł Rzeszuciński .

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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© 2014 Springer-Verlag Berlin Heidelberg

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Rzeszuciński, P., Ottewill, J.R. (2014). Parallel Autoregressive Modeling as a Tool for Diagnosing Localized Gear Tooth Faults. 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_17

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  • DOI: https://doi.org/10.1007/978-3-642-39348-8_17

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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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