Journal ArticleDOI
The spectral kurtosis: a useful tool for characterising non-stationary signals
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TLDR
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.About:
This article is published in Mechanical Systems and Signal Processing.The article was published on 2006-02-01. It has received 974 citations till now.read more
Citations
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Diagnostics of machines and structures: dynamic identification and damage detection
TL;DR: In this paper, a Principal Component Analysis (PCA)-based method for damage detection of a bearing diagnostic application is considered. But the application of the PCA-based method is limited by memory limitation problems, and two alternative techniques are developed and demonstrated on numerical and experimental applications.
Journal ArticleDOI
The MFBD: a novel weak features extraction method for rotating machinery
TL;DR: In this article, a weak feature extraction method based on used as a good filtermultiple frequency bands demodulation was proposed for weak fault signal extraction, which shows good engineering significance for fault diagnosis of rotating machinery and passive detection of propeller.
Proceedings ArticleDOI
Verification of measuring the bearing clearance using kurtosis, recurrences and neural networks and comparison of these approaches
TL;DR: In this article, the determination and in situ detection of bearing radial clearance using vibration spectra detected by acceleration sensors applied to double-row self-aligning ball bearings is studied using neural networks, calculating the spectral kurtosis of corresponding spectra and performing recurrence plots and recurrence quantification analysis for various bearing clearances.
Journal ArticleDOI
Bearing fault detection using motor current signal analysis based on wavelet packet decomposition and Hilbert envelope
TL;DR: In this paper, a new approach for rolling element bearing diagnosis without slip estimation, based on the wavelet packet decomposition (WPD) and the Hilbert transform, was presented, which extracts the envelope of the motor current signal, which contains bearings fault-related frequency information.
Dissertation
Contribution au diagnostic de machines électromagnétiques : exploitation des signaux électriques et de la vitesse instantanée
TL;DR: In this paper, the diagnostic des defauts mecaniques des machines electromecaniques par traitement des signaux electriques (courants and tensions) issus des telles machines and recus sur un ensemble des capteurs, and essayer d'extraire et de separer les differentes composantes, electrique ou mecanique, which existent.
References
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Book
Probability, random variables and stochastic processes
TL;DR: This chapter discusses the concept of a Random Variable, the meaning of Probability, and the axioms of probability in terms of Markov Chains and Queueing Theory.
Book
Probability, random variables, and stochastic processes
TL;DR: In this paper, the meaning of probability and random variables are discussed, as well as the axioms of probability, and the concept of a random variable and repeated trials are discussed.
Journal ArticleDOI
Tutorial on higher-order statistics (spectra) in signal processing and system theory: theoretical results and some applications
TL;DR: A compendium of recent theoretical results associated with using higher-order statistics in signal processing and system theory is provided, and the utility of applying higher- order statistics to practical problems is demonstrated.
Journal ArticleDOI
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.
Related Papers (5)
The spectral kurtosis: application to the vibratory surveillance and diagnostics of rotating machines
Jérôme Antoni,Robert B. Randall +1 more