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A Method of Discriminating Fault against Oscillation Based on Empirical Mode Decomposition

机译:基于经验模态分解的振动故障识别方法

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Power system oscillation is always causing wrong operation of distance protection. So it is necessary to discriminate between power fault and system oscillation. Because the fault voltage is a peaked wave with nonstationary component, it can be distinguished from oscillation voltage by the characteristics of amplitude and frequency variable. A new method based on empirical mode decomposition(EMD) was developed. EMD separated the phase voltage series to components with diu000berent time scale, say, intrinsic mode function( IMF), which eliminated the spurious harmonics and provided high-resolution time-frequency characteristics of system’s diu000berent work states. To demonstrate the performance of proposed scheme, various voltage signals of power system were identified. The results show that EMD has a significant potential in discriminating fault against oscillation disturbed by colored noises.
机译:电力系统的振荡总是会导致距离保护的错误操作。因此有必要区分电源故障和系统振荡。由于故障电压是具有非平稳分量的峰值波,因此可以通过振幅和频率变量的特性将其与振荡电压区分开。提出了一种基于经验模态分解(EMD)的新方法。 EMD将相电压序列分离为具有固有时间尺度的组件,例如固有模式函数(IMF),它消除了寄生谐波,并提供了系统处于异常工作状态的高分辨率时频特性。为了证明所提方案的性能,确定了电力系统的各种电压信号。结果表明,EMD在鉴别故障方面有很大的潜力,可以防止有色噪声干扰振荡。

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