基于正弦信号固有特征的故障选相研究

为快速准确识别高压输电线路短路故障，提出一种故障检测与选相的新方法。基于正弦信号经矩阵变换时移不变的特性，应用4采样点短数据窗的矩阵行列式变换函数，动态滑动窗口进行短路故障检测。对采集的各相电流电压值经短时动态去噪后计算其矩阵变换函数K系数值，通过K值与阈值的比较识别故障类型。在Matlab/Simulink下搭建220 kV双端电源输电系统短路故障模型进行验证，结果表明，该方法能在不同条件下准确识别短路故障，具有较高的灵敏性、可靠性，理论上故障检测与选相不超过5 ms。

Study of fault-type identification using inherent characteristics of the sinusoidal signal

In order to identify the short-circuit fault of high-voltage transmission lines fast and accurately, a novel method for fault detection and phase selection is discussed. Based on shift invariant features of sinusoidal signals after matrix transformations, applying matrix transformation function with 4 sampling points ultra-short data window, the short-circuit fault is detected by dynamic sliding window. The sampling values of each phase current and voltage are used to calculate their K values after short-time dynamic denoising, through comparison of the K value and the threshold, the fault type is identified. A short-circuit fault model of 220 kV dual-source power transmission system is established in MATLAB/Simulink environment, simulation results show that the method has high sensitivity and reliability and it can accurately identify the short-circuit fault under different conditions, theoretically, the time of fault detection and phase selection does not exceed 5 ms.