基于模态电流分量小波细节系数的故障类型识别方法

S. Myint, W. Wichakool
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引用次数: 3

摘要

提出了基于电流行波细节系数绝对值最大值的故障分类和故障选相算法。该方法不采用阈值法,而是通过对这些分类参数进行比较来正确识别故障相位和故障类型。因此,所提出的方法可用于任何类型的配电测试系统。该方法利用离散小波变换的数学工具来解决这一问题。在环形配电系统上,通过改变故障类型、故障馈线、故障电阻、故障位置和故障发生时间来模拟各种故障情况。在MATLAB Simulink中的仿真结果验证了故障选相技术的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fault Type Identification Method based on Wavelet Detail Coefficients of Modal Current Components
This paper presents the algorithm of fault classification and faulted phase selection based on the absolute maxima values of detail coefficient of current traveling waves. The proposed method identifies the faulted-phase and fault type correctly by comparing these classification parameters to each other instead of using threshold values. Therefore, the proposed method can be used in any types of distribution test system. The proposed approach uses the mathematical tool of discrete wavelet transform to solve the problem. Various fault conditions were simulated by varying fault type, faulted-feeder, fault resistance, fault location and fault inception time, on a loop distribution system. The simulation in MATLAB Simulink results demonstrate the validity of the proposed technique of faulted phase selection.
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