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中文摘要：
单端行波故障测距的关键是正确辨识量测到的第2个行波波头的性质。当母线上最短健全线路的长度大于故障线路全长的四分之一且次短健全线路长度大于故障线路全长的二分之一时，保护安装处检测到的前3个波头一定含有至少2个来自故障线路的行波。当健全线路不满足上述条件时，用方向行波识别行波是否来自故障线路。利用人工神经网络（artificial neutral network，ANN）的非线性函数逼近拟合能力，选取保护安装处检测到的后2个波头与首波头的时间差及其波头极性作为样本属性，训练、测试ANN建立其故障测距的ANN并模型来实现初步的故障测距，然后应用故障距离与波速、传输时间的关系正确辨识第2个行波波头性质，继而求得精确的故障距离。仿真结果表明该方法可行、有效。
英文摘要：
The difficulty in applying single terminal fault location method is to identify the second wave correctly. If the length of the shortest healthy line is longer than a quarter of the faulty line and the second shortest healthy line is longer than the half of the faulty line, more than two waves that are from the faulty line must be contained in the first three traveling waves. If the healthy lines don＇t fill above requirements, the directional traveling wave is used to identify whether the wave comes from faulty line or not. The polarity of the first three waves and their time-lag were selected as the characteristic of artificial neutral network （ANN） to establish fault diagnosis model which could locate the preliminary fault distance. The relationship between fault distance and velocity, and that between fault distance and traveling wave transmission time were applied to identify the second traveling wave and obtain the accurate fault distance. Simulation results show that the presented method is feasible and effective.
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