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用于22 kV电压电力线屏蔽导体故障类型基于天线检测的数据集

Dataset for Antenna-Based Detection of Fault Types in Covered Conductors for 22 kV Voltage Power Lines.

作者信息

Kabot Ondřej, Klein Lukáš, Prokop Lukáš, Mišák Stanislav, Slanina Zdeněk

机构信息

ENET centre - CEET, VSB - Technical University of Ostrava, Ostrava, Czech Republic.

Faculty of Electric Engineering and Computer Science, VSB - Technical University of Ostrava, Ostrava, Czech Republic.

出版信息

Sci Data. 2024 Dec 4;11(1):1319. doi: 10.1038/s41597-024-04009-1.

DOI:10.1038/s41597-024-04009-1
PMID:39632837
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11618338/
Abstract

This abstract presents a dataset for the detection of fault types in XLPE-covered conductors utilized in 22 kV medium voltage power distribution systems. We employed an antenna-based approach for detecting partial discharges. The dataset encompasses 12 distinct fault categories, ranging from ground phase faults to inter-phase faults, and no-fault case with steel or covered conductor as fault. We also used three different antennas. Each sample is a single measurement from antenna, consisting of 10 data points as floating numbers. The utilization of the antenna-based method offers the potential for a more cost-effective and straightforward installation for the detection of partial discharges. The objective of dataset is to enhance the identification of fault types, thereby promoting broader adoption of covered conductors in overhead power distribution lines. Such adoption proves particularly beneficial in confined areas, including natural parks, where safety is a prime concern. It is noteworthy that this dataset represents an original contribution, as no prior publication has addressed detection for this specific range of fault types and method of detection.

摘要

本摘要介绍了一个用于检测22 kV中压配电系统中交联聚乙烯（XLPE）覆盖导体故障类型的数据集。我们采用基于天线的方法来检测局部放电。该数据集包含12种不同的故障类别，从接地相故障到相间故障，以及以钢或覆盖导体作为故障的无故障情况。我们还使用了三种不同的天线。每个样本是来自天线的一次测量，由10个作为浮点数的数据点组成。基于天线的方法的使用为局部放电检测提供了更具成本效益和更简便安装的潜力。数据集的目标是增强故障类型的识别，从而促进架空配电线路中覆盖导体的更广泛采用。这种采用在包括自然公园在内的受限区域特别有益，在这些区域安全是首要关注点。值得注意的是，这个数据集是原创成果，因为之前没有出版物涉及针对此特定故障类型范围的检测以及检测方法。

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本文引用的文献

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Sci Data. 2023 Aug 21;10(1):544. doi: 10.1038/s41597-023-02451-1.