J
Jérôme Antoni
Researcher at Institut national des sciences Appliquées de Lyon
Publications - 257
Citations - 13994
Jérôme Antoni is an academic researcher from Institut national des sciences Appliquées de Lyon. The author has contributed to research in topics: Cyclostationary process & Computer science. The author has an hindex of 44, co-authored 233 publications receiving 10965 citations. Previous affiliations of Jérôme Antoni include University of Lyon & University of Technology of Compiègne.
Papers
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Journal ArticleDOI
Rolling element bearing diagnostics—A tutorial
Robert B. Randall,Jérôme Antoni +1 more
TL;DR: This tutorial is intended to guide the reader in the diagnostic analysis of acceleration signals from rolling element bearings, in particular in the presence of strong masking signals from other machine components such as gears.
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Fast computation of the kurtogram for the detection of transient faults
TL;DR: This communication describes a fast algorithm for computing the kurtogram over a grid that finely samples the ( f, Δ f ) plane and the efficiency of the algorithm is illustrated on several industrial cases concerned with the detection of incipient transient faults.
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The spectral kurtosis: application to the vibratory surveillance and diagnostics of rotating machines
Jérôme Antoni,Robert B. Randall +1 more
TL;DR: In this article, the spectral kurtosis (SK) was used to detect and characterize nonstationary signals in the presence of strong masking noise and to detect incipient faults in rotating machines.
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The spectral kurtosis: a useful tool for characterising non-stationary signals
TL;DR: A formalisation of the spectral kurtosis by means of the Wold–Cramer decomposition of “conditionally non-stationary” processes is proposed, which engenders many useful properties enjoyed by the SK.
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The relationship between spectral correlation and envelope analysis in the diagnostics of bearing faults and other cyclostationary machine signals
TL;DR: In this article, it was shown that the spectral correlation can be interpreted as a Fourier transform of the average squared envelope of the signal, which is much easier to obtain directly.