It is difficult for conventional relaying algorithms to detect incipient faults, such as insulator current leakage, electrical faults due to tree limbs, and transient or intermittent earth faults, which are frequent in distribution networks. With the time, they may lead to a catastrophic failure. In order to avoid this situation, S-transform technique is proposed to extract the suitable features of incipient fault in this chapter. A least square support vector machine (LS-SVM) classifier is developed utilizing the features so that incipient fault is distinguished from the normal disturbances. Then the polarity of magnitude difference of residual current is used to determine the fault section of distribution network. The proposed technique has been investigated by ATP/EMTP simulation software. Simulation results show that this technique is effective and robust.
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机译：对于常规继电算法而言，很难检测出配电网中经常出现的初始故障，例如绝缘子电流泄漏，由于树枝引起的电气故障以及瞬时或间歇性接地故障。随着时间的流逝，它们可能会导致灾难性的失败。为了避免这种情况，本章提出了S变换技术来提取早期故障的合适特征。利用这些特征开发了最小二乘支持向量机（LS-SVM）分类器，以便将初始故障与正常干扰区分开。然后利用剩余电流幅度差的极性确定配电网的故障区域。 ATP / EMTP仿真软件对提出的技术进行了研究。仿真结果表明，该技术是有效且鲁棒的。
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