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Empirical Mode Decomposition Based DC Fault Detection Method in Multi-terminal DC System

机译:基于经验模式分解的多终端直流系统的DC故障检测方法

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The rapid rising rate of dc line current after the dc fault inception in the high voltage dc (HVDC) system proposes a high requirement on the response speed of dc fault detection methods. In this paper, a new detection method based on empirical mode decomposition (EMD) is proposed. Unlike traditional parameters including time and frequency, EMD tries to describe the signal by characteristic time scale (CTS) which is suited to analyze non-linear and non-stationary signals such as the fault current. The principle and procedure of this method is illustrated in detail. Generally, this method could detect the dc fault within 0.2 ms with enough discrimination to distinguish the fault line and fault-free lines on the 4-bus ring multi-terminal dc (MTDC) system in MATLAB/Simulink. In addition, this method could retain its validity free from the interference of noise and filtering. Moreover, a comparison of this EMD based method between wavelet transform (WT) and short time Fourier transform (STFT) is also made to show its fast detection speed.
机译:高压DC(HVDC)系统DC故障初始在高压DC(HVDC)系统中的直流线电流的快速上升率提出了对DC故障检测方法的响应速度的高要求。本文提出了一种基于经验模式分解(EMD)的新检测方法。与包括时间和频率的传统参数不同,EMD尝试通过特征时间尺度(CTS)来描述信号,其适用于分析非线性和非静止信号,例如故障电流。该方法的原理和过程详细说明。通常,该方法可以通过足够的识别来检测0.2ms内的直流故障,以区分Matlab / Simulink在4母环多终端DC(MTDC)系统上的故障线和故障线。此外,此方法可以保留其有效性免于噪声和滤波的干扰。此外,还使小波变换(WT)和短时间傅里叶变换(STFT)之间的该基于EMD方法的比较以显示其快速检测速度。

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