A real-time algorithm for the harmonic estimation and frequency tracking of dominant components in fusion plasma magnetic diagnostics

Abstract

The real-time tracking of instantaneous quantities such as frequency, amplitude, and phase of components immerse in noisy signals has been a common problem in many scientific and engineering fields such as power systems and delivery, telecommunications, and acoustics for the past decades. In magnetically confined fusion research, extracting this sort of information from magnetic signals can be of valuable assistance in, for instance, feedback control of detrimental magnetohydrodynamic modes and disruption avoidance mechanisms by monitoring instability growth or anticipating mode-locking events. This work is focused on nonlinear Kalman filter based methods for tackling this problem. Similar methods have already proven their merits and have been successfully employed in this scientific domain in applications such as amplitude demodulation for the motional Stark effect diagnostic. In the course of this work, three approaches are described, compared, and discussed using magnetic signals from the Joint European Torus tokamak plasma discharges for benchmarking purposes.