An application of the shortest path algorithm for the identification of weak MHD mode

Abstract

Identification of magnetohydrodynamic (MHD) modes is a crucial issue in the control of magnetically confined plasmas. This paper proposes a novel method for identifying the evolution of MHD modes from a signal with a low signal-to-noise ratio. The proposed method generates a weighted directed graph from the time-frequency spectrum and calculates the evolution of the mode frequency by solving the shortest path. This method addresses the limitations posed by the lack of data channels and the disturbance of noise in the estimation of mode frequency and yields much better results compared to traditional methods. It is demonstrated that this method figured out the evolution of an unlocked tearing mode superiorly on the J-TEXT tokamak. The uncertainty of this method proves feasible even if the signal-to-noise ratio of the signal is as low as 0.5. Furthermore, with appropriate parameters, this method can be applied to not only signals with MHD modes but also general signals with continuous modes.