MHD Mode Identification from Mirnov Coils Signals in Tokamak Via Combination of Singular Value Decomposition and Hilbert–Huang Transform Analysis Methods

Abstract

In this work, we investigate how to study the MHD activities in Tokamak plasma via the combination of singular value decomposition (SVD) and Hilbert–Huang transform (HHT) methods. We apply this approach to the Mirnov coil signal fluctuations analysis without any filtering technique. First, the principal axes (PAs) of a pick-up Mirnov signals are extracted by SVD analysis. Next, the harmonics of dominants PAs is obtained by empirical mode decomposition (EMD) analysis. Moreover, the time–frequency behavior of Mirnov signals are extracted by HHT. The proposed technique is employed to analyze Mirnov coils signals for mode type and frequency identification, especially in multimode MHD activities. We obtained Spatial–temporal structures of the Mirnov coils fluctuations in terms of correlation functions to better identification of mode number and frequencies of dominant MHD modes. We also present the results of this method applied to IR-T1 and Golem Tokamaks Mirnov coils signals. Consequently, satisfying results from SVD + HHT analysis method and spatial–temporal structures for IR-T1 and Golem Tokamaks Mirnov data observed.