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
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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.Abstract:
A new method for analysing nonlinear and non-stationary data has been developed. The key part of the method is the empirical mode decomposition method with which any complicated data set can be dec...read more
Citations
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Efficient Heart Sound Segmentation and Extraction Using Ensemble Empirical Mode Decomposition and Kurtosis Features
TL;DR: An efficient heart sound segmentation method that automatically detects the location of first ( S1) and second ( S2) heart sound and extracts them from heart auscultatory raw data is presented here and paves the way for further exploitation of the diagnostic value of heart sounds in everyday clinical practice.
Journal ArticleDOI
2D Empirical Transforms. Wavelets, Ridgelets, and Curvelets Revisited
TL;DR: This paper revisits some well-known transforms of wavelet transform and shows that it is possible to build their empirical counterparts and proves that such constructions lead to different adaptive frames which show some promising properties for image analysis and processing.
Journal ArticleDOI
Quantitative diagnosis of a spall-like fault of a rolling element bearing by empirical mode decomposition and the approximate entropy method
TL;DR: In this article, the authors applied the approximate entropy (ApEn) method and empirical mode decomposition (EMD) to clearly separate the entry-exit events, and thus the size of the spall-like fault is estimated.
Journal ArticleDOI
Detecting anomalies in beams and plate based on the Hilbert Huang transform of real signals
TL;DR: In this paper, the feasibility of the Hilbert-Huang transform (HHT) as a signal processing tool for locating an anomaly, in the form of a crack, delamination, stiffness loss or boundary in beams and plate, based on physically acquired propagating wave signals.
Journal ArticleDOI
Research and application of improved adaptive MOMEDA fault diagnosis method
Zhijian Wang,Zhijian Wang,Wenhua Du,Junyuan Wang,Jie Zhou,Xiaofeng Han,Ziying Zhang,Lei Huang +7 more
TL;DR: The article preprocesses the composite fault with ensemble empirical mode decomposition (EEMD) and then reconstructs the intrinsic mode function with the same time scale and proposes kurtosis spectral entropy as the objective function and uses the proposed method to search the complex fault pulse signals in strong noise environment.
References
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TL;DR: In this paper, the authors used the representations of the noise currents given in Section 2.8 to derive some statistical properties of I(t) and its zeros and maxima.
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