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Improved mathematical morphology transformation and application to single ground fault feature extraction in small current system

机译:改进的数学形态学变换及其在小电流系统单接地故障特征提取中的应用

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Single phase grounding fault occurs in small current grounding power system frequently, fault signal caused by which contains a large number of feature information, which is an important basis for the fault location. However, due to the weakness of the fault signal, collecting the fault feature information becomes a difficult point to detect the fault line and solve the fault location. In this paper, combining with the idea of multi-resolution structural elements, an improved mathematical morphology method to accomplish the extraction of the characteristics of the fault signal has been proposed. Firstly, the consistency distribution level has been introduced to ameliorate the traditional morphological filter, which reassigned the individual treatment effect of the signal of Open-Closing and Close-Opening operation and optimized the proportional coefficients of these two kinds of operations in this filter. As a result, it makes these two operations have a more thorough and effective influence on the feature signal extraction results. Then, it has taken the use of the principle of multi-resolution structural elements to complete feature extraction by choosing different kinds of linear structure element. By the simulation experiment, compared with the fault feature component extracted by wavelet transform, it shows that this measures has a good effect on the fault feature extraction of single phase grounding fault in neutral ineffective grounding system.
机译:小电流接地电力系统中单相接地故障频繁发生,由此引起的故障信号包含大量的特征信息,这是进行故障定位的重要依据。然而,由于故障信号的弱点,收集故障特征信息成为检测故障线和解决故障位置的难点。本文结合多分辨率结构元素的思想,提出了一种改进的数学形态学方法来完成故障信号特征的提取。首先,引入一致性分布级别以改善传统的形态滤波器,它重新分配了开闭操作和闭开操作信号的个别处理效果,并在此滤波器中优化了这两种操作的比例系数。结果,这使得这两个操作对特征信号提取结果具有更彻底和有效的影响。然后,它利用多分辨率结构元素的原理通过选择不同种类的线性结构元素来完成特征提取。通过仿真实验,与小波变换提取的故障特征分量相比,表明该措施对中性点无效接地系统单相接地故障的故障特征提取具有良好的效果。

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