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Identification of harmonics and sidebands in a finite set of spectral components

Timothée Gerber 1 Nadine Martin 1 Corinne Mailhes 2, 3 
1 GIPSA-SAIGA - GIPSA - Signal et Automatique pour la surveillance, le diagnostic et la biomécanique
GIPSA-DA - Département Automatique, GIPSA-DIS - Département Images et Signal
2 IRIT-SC - Signal et Communications
IRIT - Institut de recherche en informatique de Toulouse
Abstract : Spectral analysis along with the detection of harmonics and modulation sidebands are key elements in condition monitoring systems. Several spectral analysis tools are already able to detect spectral components present in a signal. The challenge is therefore to complete this spectral analysis with a method able to identify harmonic series and modulation sidebands. Compared to the state of the art, the method proposed takes the uncertainty of the frequency estimation into account. The identification is automatically done without any a priori, the search of harmonics is exhaustive and moreover the identification of all the modulation sidebands of each harmonic is done regardless of their energy level. The identified series are characterized by criteria which reflect their relevance and which allow the association of series in families, characteristic of a same physical process. This method is applied on real-world current and vibration data, more or less rich in their spectral content. The identification of sidebands is a strong indicator of failures in mechanical systems. The detection and tracking of these modulations from a very low energy level is an asset for earlier detection of the failure. The proposed method is validated by comparison with expert diagnosis in the concerned fields.
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Submitted on : Wednesday, July 24, 2013 - 4:33:31 PM
Last modification on : Tuesday, June 14, 2022 - 12:12:47 PM
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  • HAL Id : hal-00845120, version 2


Timothée Gerber, Nadine Martin, Corinne Mailhes. Identification of harmonics and sidebands in a finite set of spectral components. CM 2013 - MFPT 2013 - 10th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies, Jun 2013, Krakow, Poland. ⟨hal-00845120v2⟩



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