Journal ArticleDOI
Hilbert transform in vibration analysis
TLDR
In this article, a tutorial on Hilbert transform applications to mechanical vibration is presented, with a large number of examples devoted to illustrating key concepts on actual mechanical signals and demonstrating how the Hilbert transform can be taken advantage of in machine diagnostics, identification of mechanical systems and decomposition of signal components.About:
This article is published in Mechanical Systems and Signal Processing.The article was published on 2011-04-01. It has received 553 citations till now. The article focuses on the topics: Hilbert–Huang transform & Hilbert transform.read more
Citations
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Journal ArticleDOI
Ensemble empirical mode decomposition: a noise-assisted data analysis method
Zhaohua Wu,Norden E. Huang +1 more
TL;DR: The effect of the added white noise is to provide a uniform reference frame in the time–frequency space; therefore, the added noise collates the portion of the signal of comparable scale in one IMF.
Journal ArticleDOI
On instantaneous frequency
TL;DR: This paper offers an overview of the difficulties involved in using AS, and two new methods to overcome the difficulties for computing IF, and finds that the NHT and direct quadrature gave the best overall performance.
Journal ArticleDOI
Gearbox condition monitoring in wind turbines: A review
TL;DR: A review on different methods and techniques for gearbox condition monitoring in wind turbines aiming to increase lifetime expectancy of components while reducing operation and maintenance cost is gathered.
Journal ArticleDOI
Monitoring and processing signal applied in machining processes – A review
TL;DR: In this article, the first steps involved in choosing and defining various techniques that may be used to monitor machining processes are discussed, and the techniques to acquire and process the signals of the monitoring processes are outlined.
Journal ArticleDOI
Convolutional neural network-based hidden Markov models for rolling element bearing fault identification
TL;DR: In this article, a convolutional neural network-based hidden Markov models (CNN HMMs) are presented to classify multi-fault in mechanical systems, and the average classification accuracy ratios are 98.125% and 98% for two data series with agreeable error rate reductions.
References
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Journal ArticleDOI
The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis
Norden E. Huang,Zheng Shen,Steven R. Long,Man-Li C. Wu,Hsing H. Shih,Quanan Zheng,Nai-Chyuan Yen,C. C. Tung,Henry H. Liu +8 more
TL;DR: In this paper, a new method for analysing nonlinear and nonstationary data has been developed, which is the key part of the method is the empirical mode decomposition method with which any complicated data set can be decoded.
Journal ArticleDOI
Smoothing and Differentiation of Data by Simplified Least Squares Procedures.
Journal ArticleDOI
Ensemble empirical mode decomposition: a noise-assisted data analysis method
Zhaohua Wu,Norden E. Huang +1 more
TL;DR: The effect of the added white noise is to provide a uniform reference frame in the time–frequency space; therefore, the added noise collates the portion of the signal of comparable scale in one IMF.
Book
Vibration problems in engineering
TL;DR: In this article, the Probleme dynamique and Vibration were used for propagation of ondes reference records created on 2004-09-07, modified on 2016-08-08.
Related Papers (5)
The spectral kurtosis: application to the vibratory surveillance and diagnostics of rotating machines
Jérôme Antoni,Robert B. Randall +1 more