Fault data set

The dataset belongs to features of high-impedance faults (HIF) and other faults/switching transients in Microgrid (MG) power networks. The features are originally extracted from simulated fault and transient current signals with the help of Discrete Wavelet Transform (using Matlab-Simulink). These features are then used to train Machine learning algorithms to classify HIF and other transients in MG system.
Class: Normal (no fault); LG (line to ground); LLG (line-line to ground); LLLG (all three phases to ground); LL (line to line); HIF (high impedance fault); CS (capacitor switching transient); LS (Load switching transient)
EA-Energy features from phase A (of each class event)
EB-Energy features from phase B (of each class event)
EC-Energy features from phase C (of each class event)

本数据集收录了微电网（Microgrid, MG）电力网络中的高阻抗故障（high-impedance faults, HIF）及其他故障、开关暂态过程的特征数据。上述特征最初通过离散小波变换（Discrete Wavelet Transform，依托Matlab-Simulink工具）从模拟故障与暂态电流信号中提取获得。随后，这些特征被用于训练机器学习算法，以实现微电网系统内高阻抗故障与其他暂态过程的分类任务。
类别设置如下：正常状态（Normal，无故障）；LG（单相接地故障，line to ground）；LLG（两相接地故障，line-line to ground）；LLLG（三相接地故障，all three phases to ground）；LL（两相相间故障，line to line）；HIF（高阻抗故障，high impedance fault）；CS（电容器开关暂态，capacitor switching transient）；LS（负荷开关暂态，Load switching transient）。
EA：各类别事件对应A相的能量特征；
EB：各类别事件对应B相的能量特征；
EC：各类别事件对应C相的能量特征。

搜集汇总

背景与挑战

背景概述

该数据集包含微电网电力网络中高阻抗故障和其他故障/开关瞬态的特征，通过离散小波变换提取，用于机器学习分类。数据集涵盖多种故障类型和瞬态事件，以及各相的能量特征，适用于电气工程和故障诊断研究。