A Data Set of Signals from an Antenna for Detection of Partial Discharges in Overhead Insulated Power Line

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27740%2F23%3A10253251" target="_blank" >RIV/61989100:27740/23:10253251 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/61989100:27730/23:10253251 RIV/61989100:27240/23:10253251

Výsledek na webu

<a href="https://www.nature.com/articles/s41597-023-02451-1" target="_blank" >https://www.nature.com/articles/s41597-023-02451-1</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1038/s41597-023-02451-1" target="_blank" >10.1038/s41597-023-02451-1</a>

Jazyk výsledku

angličtina

Název v původním jazyce

A Data Set of Signals from an Antenna for Detection of Partial Discharges in Overhead Insulated Power Line

Popis výsledku v původním jazyce

We introduce a data set obtained via a contactless antenna method for detecting partial discharges in XLPE-covered conductors used in medium-voltage overhead power transmission lines. The data set consists of almost three years&apos; worth of data, collected every hour from 9 measuring stations in Czechia and Slovakia. Each sample in the data set represents a single signal gathered for 20 ms. The contactless method is deployed on the same stations as the galvanic contact method, which is used by power distributors and can provide ground truth. Also manually curated data by human expert are present. Successful detection of partial discharges can prevent electricity shutdowns and forest fires resulting from insulation failure due to vegetation contact. The data set is particularly relevant for covered conductors used in mountainous regions where establishing a safe zone is challenging. The contactless method offers advantages such as cheaper and easier installation. The data set has the potential to develop machine learning models to detect partial discharges and facilitate safer and cheaper use of covered conductors.

Název v anglickém jazyce

A Data Set of Signals from an Antenna for Detection of Partial Discharges in Overhead Insulated Power Line

Popis výsledku anglicky

We introduce a data set obtained via a contactless antenna method for detecting partial discharges in XLPE-covered conductors used in medium-voltage overhead power transmission lines. The data set consists of almost three years&apos; worth of data, collected every hour from 9 measuring stations in Czechia and Slovakia. Each sample in the data set represents a single signal gathered for 20 ms. The contactless method is deployed on the same stations as the galvanic contact method, which is used by power distributors and can provide ground truth. Also manually curated data by human expert are present. Successful detection of partial discharges can prevent electricity shutdowns and forest fires resulting from insulation failure due to vegetation contact. The data set is particularly relevant for covered conductors used in mountainous regions where establishing a safe zone is challenging. The contactless method offers advantages such as cheaper and easier installation. The data set has the potential to develop machine learning models to detect partial discharges and facilitate safer and cheaper use of covered conductors.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

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OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

<a href="/cs/project/TN02000025" target="_blank" >TN02000025: Národní centrum pro energetiku II</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2023

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Scientific data

ISSN

2052-4463

e-ISSN

2052-4463

Svazek periodika

10

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

10

Strana od-do

"August 2023"

Kód UT WoS článku

001074358600004

EID výsledku v databázi Scopus

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