Design and implementation of plasma electron density measurements based on FPGA with all-phase FFT for tokamak devices

Abstract

Plasma electron density is one of the most fundamental parameters when studying tokamak plasma physics, which is widely used in plasma control systems and plasma physics analyses. A hydrogen cyanide laser interferometer is generally applied to measure the plasma electron density in many tokamak devices. Therein, the plasma electron density is calculated by measuring the phase difference between the reference signal and the detector signal. This work provides a new way to realize real-time measurements of the plasma electron density with a phase comparator and processing system based on a field-programmable gate array chip. The system integrates a signal processing module, an all-phase fast Fourier transform (ap-FFT) module realized via matrix operations and phase comparisons, and a network communication module all in one board. This work concludes that the ap-FFT is robust and accurate for phase calculations compared with a windowing FFT. A data-reuse method and a phase shift method are proposed to improve the time resolution and phase range. The phase error is less than 0.1° and the time resolution is 0.025 ms, which is better than hardware methods and traditional software methods. This system is highly flexible with reduced design costs to meet the requirements of a tokamak, which can provide a valuable reference for other tokamak and phase difference comparisons.

Power System Signal-Detection Method Based on the Accelerated Unsaturated Stochastic Resonance Principle

“…Analyzing the parameters of harmonics to obtain real-time and accurate harmonic data is key to harmonic detection. Currently, power system harmonic analysis primarily relies on time-domain analysis [5], frequency-domain analysis [6], wavelet transform method [7], and Hilbert-Huang transform method [8]. In classical time-frequency domain analysis methods, spectral overlap occurs when weak power harmonic signals are overwhelmed by a wide spectrum of strong background noise.…”

“…The frequency domain analysis method has issues such as the window function and the complexity and difficulty of designing the correction method. The study [6] utilizes the improved ap-FFT ratio method for spectral correction, which has a simple correction formula and is easy to implement, but when correcting the amplitude, only the strongest spectral line near the actual frequency point is utilized for the interpolation correction, while the information of the second strongest spectral line is not utilized, and the accuracy of the detection results cannot be guaranteed when the number of sample points does not meet the sufficiently large conditions. The wavelet transform is prone to band aliasing in harmonic decomposition and also has issues such as a large computational workload.…”