基于统计特征的输电故障识别与分类

2022 IEEE 2nd International Conference on Sustainable Energy and Future Electric Transportation (SeFeT) Pub Date : 2022-08-04 DOI:10.1109/SeFeT55524.2022.9908816

Pabitra Kumar Barman, N. Subhrahmanyam, Saptarshi Roy, N. Babu

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引用次数: 0

摘要

本文提出了一种利用分析技术诊断输电系统故障的有效算法。在这项工作中使用了现场数据集。统计工具已经被用来确定从线电流Perk的矢量模数中提取的特征集。采用模糊逻辑对故障状态和健康状态进行分类。从混淆矩阵可以看出，该算法几乎在所有情况下都能得到准确的值(>95%)，证明了算法的准确性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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A Statistical Feature-Based Transmission Fault Identification and Classification

This paper presents an efficient algorithm for diagnosing the transmission faults using analytical techniques. An on-site dataset is used in this work. Statistical tools have been adapted to determine the feature set extracted from line current Perk’s vector modulus. Fuzzy logic is incorporated for the classification of faulty and healthy conditions. From the confusion matrix, it is proven that this algorithm has been proven to be accurate as it results accurate values in almost all the cases (>95%).

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来源期刊

2022 IEEE 2nd International Conference on Sustainable Energy and Future Electric Transportation (SeFeT)

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