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Journal ArticleDOI

Application of the Variational-Mode Decomposition for Seismic Time–frequency Analysis

TLDR
Application of the VMD on field data demonstrates that instantaneous spectrum after VMD targets the thickness variation in the coal seam more sensitively than the conventional tools and highlights the fine details that might escape unnoticed.
Abstract
Seismic time–frequency analysis methods play an important role in seismic interpretation for its superiority in significantly revealing the frequency content of a seismic signal changes with time variation. Variational-mode decomposition (VMD) is a newly developed methodology for decomposition on adaptive and quasi-orthogonal signal and can decompose a seismic signal into a number of band-limited quasi-orthogonal intrinsic mode functions (IMFs). Each mode is an AM–FM signal with the narrow-band property and nonnegative smoothly varying instantaneous frequencies. Analysis on synthetic and real data shows that this method is more robust to noise and has stronger local decomposition ability than the empirical mode decomposition (EMD)-based methods. Comparing with the short-time Fourier transform (STFT) or wavelet transform (WT), instantaneous spectrum after VMD promises higher spectral and spatial resolution. Application of the VMD on field data demonstrates that instantaneous spectrum after VMD targets the thickness variation in the coal seam more sensitively than the conventional tools and highlights the fine details that might escape unnoticed. The technique is more promising for seismic signal processing and interpretation.

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Citations
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Journal ArticleDOI

Hybrid wind energy forecasting and analysis system based on divide and conquer scheme: A case study in China

TL;DR: A hybrid wind energy forecasting and analysis system including a deterministic forecasting module and an uncertainty analysis module to mitigate the challenges in existing studies is developed and could not only be used as an effective tool for wind energy Deterministic forecasting and uncertainty analysis, but also for other engineering application areas in the future.
Journal ArticleDOI

A hybrid approach to fault diagnosis of roller bearings under variable speed conditions

TL;DR: Results of this numerical simulation show the sparsity and concentration of the VTFR are better than those of short-time Fourier transform, continuous wavelet transform, Hilbert–Huang transform and Wigner–Ville distribution techniques.
Journal ArticleDOI

Denoising of UHF PD signals based on optimised VMD and wavelet transform

TL;DR: A novel denoising method namely optimised variation mode decomposition and wavelet (OVMDW) is developed, which can remove various interferences from UHF PD signals and preserve quite well the features of original signals.
Journal ArticleDOI

Thermally-induced error compensation of spindle system based on long short term memory neural networks

TL;DR: In this article, the applicability of long short term memory (LSTM) neural networks for the training of the error model is proved and the error compensation is carried out from the view of error mechanism of spindle systems to increase the thermal stability of machine tools.
References
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Book

A wavelet tour of signal processing

TL;DR: An introduction to a Transient World and an Approximation Tour of Wavelet Packet and Local Cosine Bases.
Journal ArticleDOI

Ensemble empirical mode decomposition: a noise-assisted data analysis method

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

Variational Mode Decomposition

TL;DR: This work proposes an entirely non-recursive variational mode decomposition model, where the modes are extracted concurrently and is a generalization of the classic Wiener filter into multiple, adaptive bands.
Journal ArticleDOI

Localization of the complex spectrum: the S transform

TL;DR: The S transform is shown to have some desirable characteristics that are absent in the continuous wavelet transform, and provides frequency-dependent resolution while maintaining a direct relationship with the Fourier spectrum.
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