Berthil cepstrum: a novel vibration analysis method based on marginal Hilbert spectrum applied to artificial motor aging

Abstract

Motor age determination as a part of condition monitoring heavily employs vibration analysis. This study introduces a new method for such analysis, based on concepts of cepstrum and marginal Hilbert spectrum. This new method, named Berthil cepstrum, may be applied in general signal processing, not only when vibration signals are concerned. Classical marginal Hilbert spectrum has also been applied to the artificial motor aging data with excellent results. Furthermore, a ranking of known spectrum-based methods for determination of motor age together with the new methods introduced in this study has been made based on SVM and RELIEF attribute ranking, showing quality of the new methods.

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Abbreviations

AMIF:

Automutual information function

EMD:

Empirical mode decomposition

H\(^{3}\)VD:

Hilbert–Hurst–Higuchi vibration decomposition

HHT:

Hilbert–Huang transform

HVD:

Hilbert vibration decomposition

IMF:

Intrinsic mode function

PSD:

Power spectral density

SVM:

Support vector machine

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Acknowledgements

The authors express their deepest gratitude to Prof. B.R. Upadhyaya and his team at the University of Tennessee, Nuclear Engineering Dept. for allowing use of the experimental data used here.

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Correspondence to Harun Šiljak.

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Šiljak, H., Subasi, A. Berthil cepstrum: a novel vibration analysis method based on marginal Hilbert spectrum applied to artificial motor aging. Electr Eng 100, 1039–1046 (2018). https://doi.org/10.1007/s00202-017-0566-7

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Keywords

  • Hilbert transform
  • Cepstrum
  • Vibration
  • Condition monitoring
  • Artificial motor aging