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Journal ArticleDOI

Fast computation of the kurtogram for the detection of transient faults

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TLDR
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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This article is published in Mechanical Systems and Signal Processing.The article was published on 2007-01-01. It has received 1130 citations till now. The article focuses on the topics: Fast Fourier transform.

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Citations
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Journal ArticleDOI

Rolling element bearing diagnostics—A tutorial

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.
Journal ArticleDOI

Rolling element bearing diagnostics using the Case Western Reserve University data: A benchmark study

TL;DR: Though intended primarily as a benchmark to aid in testing new diagnostic algorithms, it is also hoped that much of the discussion will have broader applicability to other bearing diagnostics cases.
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The enhancement of fault detection and diagnosis in rolling element bearings using minimum entropy deconvolution combined with spectral kurtosis

TL;DR: In this article, the minimum entropy deconvolution (MED) technique was used to enhance the surveillance capability of the spectral kurtosis (SK) by using a spalled inner race bearing.
Journal ArticleDOI

A novel method for the optimal band selection for vibration signal demodulation and comparison with the Kurtogram

TL;DR: In this paper, the authors proposed a method based on the kurtosis of the envelope spectrum amplitudes of the demodulated signal, rather than on the filter time signal, to detect transients with smaller signal-to-noise ratio comparing to the spectral kurtogram.
Journal ArticleDOI

The infogram: Entropic evidence of the signature of repetitive transients

TL;DR: It is demonstrated that the joint consideration of the infograms significantly extends the domain of applicability of the kurtogram, in particular to situations corrupted with impulsive noise or when the relaxation time of the transients is low as compared to their rate of repetition.
References
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Journal ArticleDOI

The spectral kurtosis: application to the vibratory surveillance and diagnostics of rotating machines

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.
Journal ArticleDOI

Application of the wavelet transform in machine condition monitoring and fault diagnostics: a review with bibliography

TL;DR: The application of the wavelet transform for machine fault diagnostics has been developed for last 10 years at a very rapid rate as mentioned in this paper, and a review on all of the literature is certainly not possible.
Journal ArticleDOI

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.
Journal ArticleDOI

Gearbox fault diagnosis using adaptive wavelet filter

TL;DR: In this article, an adaptive wavelet filter based on Morlet wavelet is introduced to detect early fatigue tooth crack in a gearbox with early fatigue teeth crack using the kurtosis maximization principle.
Proceedings ArticleDOI

Detection of non-Gaussian signals by frequency domain Kurtosis estimation

R. Dwyer
TL;DR: This work has considered sinusoidal and narrowband Gaussian signals which, when propagated through fading or multipath environments, are received as non-Gaussian in terms of a frequency domain Kurtosis estimate.
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