Robust Spectral Peaks Detection in Vibration and Acoustic Signals

This article brings a practical solution to the problem of spectral peak detection in nonuniform spectra. It applies a robust probabilistic approach that fits the histogram of trimmed spectral data with a truncated Gamma distribution. The estimated distribution parameters are used to derive a thresh...

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Veröffentlicht in:IEEE transactions on instrumentation and measurement 2022, Vol.71, p.1-13
Hauptverfasser: Hawwari, Yasmine, Antoni, Jerome, Andre, Hugo, Marnissi, Yosra, Abboud, Dany, El-Badaoui, Mohammed
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container_title IEEE transactions on instrumentation and measurement
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creator Hawwari, Yasmine
Antoni, Jerome
Andre, Hugo
Marnissi, Yosra
Abboud, Dany
El-Badaoui, Mohammed
description This article brings a practical solution to the problem of spectral peak detection in nonuniform spectra. It applies a robust probabilistic approach that fits the histogram of trimmed spectral data with a truncated Gamma distribution. The estimated distribution parameters are used to derive a threshold through a hypothesis test in the presence of peaks. The proposed approach gains its robustness from the formulation of the no-peak distribution, while no knowledge is available about the amount of peaks in spectral data. The authors propose a preprocessing step to cope with a nonuniform spectrum. The proposed methodology is validated on both simulated and experimental vibration and acoustic signals.
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subjects Background noise
Colored noise
Engineering Sciences
Estimation
Histograms
Nonwhite noise
Probability distribution functions
Robustness
spectral peaks
Standardization
Statistical analysis
trimmed data
truncated gamma distribution
Vibration
vibration/acoustic signals
Vibrations
White noise
title Robust Spectral Peaks Detection in Vibration and Acoustic Signals
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