The SparSpec algorithm and the application to the detection of spatial periodicities in tokamaks: error weighting the penalization criterion to improve the performance of the algorithm

IF 1.3 Q3 ORTHOPEDICS Plasma Research Express Pub Date : 2021-04-28 DOI:10.1088/2516-1067/abf946
D. Testa, H. Carfantan, L. Perrone
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引用次数: 1

Abstract

A common problem in many complex physical systems is the determination of pulsation modes from irregularly sampled time-series, and there is a wealth of signal processing techniques that are being applied to post-pulse and real-time data analysis in such complex systems. The aim of this report is studying the problem of detecting discrete spatial periodicities in the spectrum of magnetic fluctuations in tokamaks, for which the optimization of the algorithm performance is essential, particularly when multiple sensors are used with different measurement uncertainties, and some of the processed output signals are then used in real-time for discharge control. The main tool used hereafter will be the SparSpec algorithm, initially devised for astrophysical purposes and already applied to the analysis of magnetic fluctuations in various tokamaks. In its baseline version, dubbed SS-H2, the SparSpec algorithm runs in currently or previously operating tokamaks (JET, TCV and Alcator C-mod), and is foreseen to be deployed for data analysis in tokamak under construction (ITER, DTT). For JET, SS-H2 regularly runs also in real-time on a 1ms clock for detecting Alfvén Eigenmodes using synchronously-measured magnetic perturbations. On JET and TCV, it was noted that often a reduced set of sensors had to be used as the measurement uncertainties were not the same for all available sensors, somewhat deteriorating the overall performance of the algorithm. Hence, as part of a major update of the SparSpec algorithm, specifically intended for accelerating the real-time performance, use of the measurement uncertainties to weight the data, the spectral window and the ensuing penalization criterion was introduced. The behaviour of this new version of the SparSpec algorithm under a variety of simulated circumstances is analysed. It is found that the implementation of SparSpec using such error weighting produces superior results to those obtained with SS-H2, both in terms of the speed and the accuracy of the calculations. A test on actual data from the JET tokamak also shows a clear improvement in the performance of the algorithm.
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SparSpec算法及其在托卡马克空间周期性检测中的应用:通过误差加权惩罚准则提高算法的性能
在许多复杂的物理系统中,一个常见的问题是从不规则采样的时间序列中确定脉动模式,并且有大量的信号处理技术正在应用于此类复杂系统中的脉冲后和实时数据分析。本文的目的是研究托卡马克磁波动谱中离散空间周期性的检测问题,优化算法的性能是至关重要的,特别是当多个传感器使用不同的测量不确定度时,然后将处理后的输出信号实时用于放电控制。今后使用的主要工具将是SparSpec算法,它最初是为天体物理学目的而设计的,已经应用于分析各种托卡马克的磁波动。在其被称为SS-H2的基线版本中,SparSpec算法可以在当前或以前运行的托卡马克(JET, TCV和Alcator C-mod)中运行,并且预计将部署在正在建设的托卡马克(ITER, DTT)中进行数据分析。对于JET, SS-H2也定期在1ms时钟上实时运行,用于使用同步测量的磁扰动检测alfv本征模式。在JET和TCV上,由于所有可用传感器的测量不确定度不同,通常必须使用一组减少的传感器,这在一定程度上恶化了算法的总体性能。因此,作为SparSpec算法的主要更新的一部分,专门用于加速实时性能,使用测量不确定度来对数据进行加权,光谱窗口和随后的惩罚标准被引入。分析了这个新版本的SparSpec算法在各种模拟环境下的行为。结果发现,使用这种误差加权的SparSpec的实现在计算速度和精度方面都优于SS-H2。对来自JET托卡马克的实际数据的测试也表明该算法的性能有明显的改善。
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来源期刊
Plasma Research Express
Plasma Research Express Energy-Nuclear Energy and Engineering
CiteScore
2.60
自引率
0.00%
发文量
15
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