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Spectral Decomposition Using the CEEMD Method: a Case Study from the Carpathian Foredeep

Kwietniak A., Cichostępski K., Kasperska M.

Acta Geophysica

2016

Vol. 64, no. 5

1525--1541

The purpose of this work is to select the optimal spectral decomposition (SD) method for channel detection in the Miocene strata of the Carpathian Fordeep, SE Poland. For analysis, two spectral decomposition algorithms were tested on 3D seismic data: the first, based on Fast Fourier Transform (FFT), and second, on Complete Ensemble Empirical Mode Decomposition (CEEMD). Additionally the results of instantaneous frequency (IF) were compared with the results of peak frequency (PF) computed after the CEEMD. Both algorithms of SD enabled us to interpret channels, but the results are marginally different, i.e. the FFT shows more coarse, linear structures, that are desirable for channel interpretation, whereas the CEEMD does not highlight these structures as clearly and shows more, what the authors believe to be, noise.

Research on PD Signals Denoising Based on EMD Method

Pei Y., Wu Y., Jia D.

Przegląd Elektrotechniczny

2012

R. 88, nr 1b

137-140

Adaptive decomposition of complex data is realized and intrinsic mode function (IMF) components that reflect different scales information are gained through empirical mode decomposition (EMD) of partial discharge (PD) signals. The gained intrinsic mode function components are reconstructed after the wavelet threshold processing to reduce the interference of noise. This partial discharge signals denoising method has achieved good effect in the processing of simulation and measured data, which proves the effectiveness and superiority of the method.

Przedfstawionbo metode adaptacyjnej dekompozycji danych złożonych na przykładzie sygnału wyładowania niezupełnego. Do usunięcia wpływu szumów wykorzystano analizę falkową.