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Signal Processing Diagnostic Tool for Rolling Element Bearings Using EMD and MED

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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

The signal processing techniques developed for the diagnostics of mechanical components operating in stationary conditions are often not applicable or are affected by a loss of effectiveness when applied to signals measured in transient conditions. In this chapter, an original signal processing tool is developed exploiting some data-adaptive techniques such as Empirical Mode Decomposition, Minimum Entropy Deconvolution and the analytical approach of the Hilbert transform. The tool has been developed to detect localized faults on bearings of traction systems of high speed trains and it is more effective to detect a fault in non-stationary conditions than signal processing tools based on envelope analysis or spectral kurtosis, which represent until now the landmark for bearings diagnostics.

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Author information

Authors and Affiliations

  1. Department of Mechanical Engineering, Politecnico di Milano, Via G. La Masa 1, 20156, Milan, Italy

    Steven Chatterton, Roberto Ricci, Paolo Pennacchi & Pietro Borghesani

Authors
  1. Steven Chatterton
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  2. Roberto Ricci
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  3. Paolo Pennacchi
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  4. Pietro Borghesani
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Corresponding author

Correspondence to Paolo Pennacchi .

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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Chatterton, S., Ricci, R., Pennacchi, P., Borghesani, P. (2014). Signal Processing Diagnostic Tool for Rolling Element Bearings Using EMD and MED. 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_32

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  • DOI: https://doi.org/10.1007/978-3-642-39348-8_32

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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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