A Data Set of Signals from an Antenna for Detection of Partial Discharges in Overhead Insulated Power Line
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’ worth of data, collected every hour from 9 measuring stations in Czechi...
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| Veröffentlicht in: | Scientific data Jg. 10; H. 1; S. 544 - 10 |
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21.08.2023
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| Abstract | 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’ 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. |
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| AbstractList | 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’ 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. Abstract 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’ 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. 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' 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.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' 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. |
| ArticleNumber | 544 |
| Author | Klein, Lukáš Prokop, Lukáš Fulneček, Jan Seidl, David Mišák, Stanislav Piecha, Marian Dvorský, Jiří |
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| Cites_doi | 10.15598/aeee.v15i1.1894 10.3390/en12112148 10.1016/j.eswa.2022.118910 10.1155/2022/1870136 10.1109/tpwrd.2021.3104746 10.1109/NPSC49263.2020.9331843 10.1109/ACCESS.2023.3268763 10.15598/aeee.v14i5.1733 10.3390/en15186521 10.1016/j.epsr.2022.107834 10.6084/m9.figshare.c.6628553.v1 10.1109/EPE51172.2020.9269171 |
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| References | Pakonen, P. Detection of Incipient Tree Faults on High Voltage Covered Conductor Lines (Tampere University of Technology, 2007). Misak, S., Kratky, M. & Prokop, L. A novel method for detection and classification of covered conductor faults. Advances in Electrical and Electronic Engineering14, https://doi.org/10.15598/aeee.v14i5.1733 (2016). KleinLAntenna contactless partial discharges detection in covered conductors using ensemble stacking neural networksExpert Syst. Appl.202321311891010.1016/j.eswa.2022.118910 Vantuch, T., Prílepok, M., Fulneček, J., Hrbáč, R. & Mišák, S. Towards the text compression based feature extraction in high impedance fault detection. Energies12, https://doi.org/10.3390/en12112148 (2019). ElmasryWWadiMEnhanced anomaly-based fault detection system in electrical power gridsInternational Transactions on Electrical Energy Systems2022202211910.1155/2022/1870136 Kaggle. Vsb power line fault detection (2019). Martinovic, T. & Fulnecek, J. Fast algorithm for contactless partial discharge detection on remote gateway device. IEEE Trans. Power Deliv. 1–1, https://doi.org/10.1109/tpwrd.2021.3104746 (2021). Leskinen, T. & Lovrencic, V. Finnish and slovene experience of covered conductor overhead lines. In CIGRE proceedings, 54–60 (2004). ElmasryWWadiMEdla-efds: A novel ensemble deep learning approach for electrical fault detection systemsElectric Power Systems Research202220710783410.1016/j.epsr.2022.107834 Misak, S., Fulnecek, J., Jezowicz, T., Vantuch, T. & Burianek, T. Usage of antenna for detection of tree falls on overhead lines with covered conductors. Adv. Electr. Electron. Eng. 15, https://doi.org/10.15598/aeee.v15i1.1894 (2017). KleinLA dataset of signals from an antenna for detection of partial discharges in overhead xlpe insulated power line202310.6084/m9.figshare.c.6628553.v1Figshare Kabot, O., Fulneček, J., Mišák, S., Prokop, L. & Vaculík, J. Partial discharges pattern analysis of various covered conductors. In 2020 21st International Scientific Conference on Electric Power Engineering (EPE), 1–5, https://doi.org/10.1109/EPE51172.2020.9269171 (2020). Wang, Y., Chiang, H.-d. & Dong, N. Power-line partial discharge recognition with hilbert-huang transform features. Energies15, https://doi.org/10.3390/en15186521 (2022). Ahmad, D., Wang, S. & Alam, M. Long short term memory based deep learning method for fault power line detection in a mv overhead lines with covered conductors. In 2020 21st National Power Systems Conference (NPSC), 1–4, https://doi.org/10.1109/NPSC49263.2020.9331843 (2020). Klein, L., Žmij, P. & Krömer, P. Partial discharge detection by edge computing. IEEE Access 1–1, https://doi.org/10.1109/ACCESS.2023.3268763 (2023). L Klein (2451_CR5) 2023 2451_CR8 2451_CR9 2451_CR6 W Elmasry (2451_CR12) 2022; 207 L Klein (2451_CR14) 2023; 213 2451_CR15 2451_CR7 2451_CR4 2451_CR2 2451_CR3 2451_CR13 2451_CR1 2451_CR10 W Elmasry (2451_CR11) 2022; 2022 |
| References_xml | – reference: Vantuch, T., Prílepok, M., Fulneček, J., Hrbáč, R. & Mišák, S. Towards the text compression based feature extraction in high impedance fault detection. Energies12, https://doi.org/10.3390/en12112148 (2019). – reference: Kaggle. Vsb power line fault detection (2019). – reference: KleinLA dataset of signals from an antenna for detection of partial discharges in overhead xlpe insulated power line202310.6084/m9.figshare.c.6628553.v1Figshare – reference: ElmasryWWadiMEnhanced anomaly-based fault detection system in electrical power gridsInternational Transactions on Electrical Energy Systems2022202211910.1155/2022/1870136 – reference: KleinLAntenna contactless partial discharges detection in covered conductors using ensemble stacking neural networksExpert Syst. Appl.202321311891010.1016/j.eswa.2022.118910 – reference: Ahmad, D., Wang, S. & Alam, M. Long short term memory based deep learning method for fault power line detection in a mv overhead lines with covered conductors. In 2020 21st National Power Systems Conference (NPSC), 1–4, https://doi.org/10.1109/NPSC49263.2020.9331843 (2020). – reference: Pakonen, P. Detection of Incipient Tree Faults on High Voltage Covered Conductor Lines (Tampere University of Technology, 2007). – reference: Misak, S., Fulnecek, J., Jezowicz, T., Vantuch, T. & Burianek, T. Usage of antenna for detection of tree falls on overhead lines with covered conductors. Adv. Electr. Electron. Eng. 15, https://doi.org/10.15598/aeee.v15i1.1894 (2017). – reference: ElmasryWWadiMEdla-efds: A novel ensemble deep learning approach for electrical fault detection systemsElectric Power Systems Research202220710783410.1016/j.epsr.2022.107834 – reference: Martinovic, T. & Fulnecek, J. Fast algorithm for contactless partial discharge detection on remote gateway device. IEEE Trans. Power Deliv. 1–1, https://doi.org/10.1109/tpwrd.2021.3104746 (2021). – reference: Misak, S., Kratky, M. & Prokop, L. A novel method for detection and classification of covered conductor faults. Advances in Electrical and Electronic Engineering14, https://doi.org/10.15598/aeee.v14i5.1733 (2016). – reference: Kabot, O., Fulneček, J., Mišák, S., Prokop, L. & Vaculík, J. Partial discharges pattern analysis of various covered conductors. In 2020 21st International Scientific Conference on Electric Power Engineering (EPE), 1–5, https://doi.org/10.1109/EPE51172.2020.9269171 (2020). – reference: Wang, Y., Chiang, H.-d. & Dong, N. Power-line partial discharge recognition with hilbert-huang transform features. Energies15, https://doi.org/10.3390/en15186521 (2022). – reference: Leskinen, T. & Lovrencic, V. Finnish and slovene experience of covered conductor overhead lines. In CIGRE proceedings, 54–60 (2004). – reference: Klein, L., Žmij, P. & Krömer, P. Partial discharge detection by edge computing. IEEE Access 1–1, https://doi.org/10.1109/ACCESS.2023.3268763 (2023). – ident: 2451_CR4 doi: 10.15598/aeee.v15i1.1894 – ident: 2451_CR7 – ident: 2451_CR9 doi: 10.3390/en12112148 – volume: 213 start-page: 118910 year: 2023 ident: 2451_CR14 publication-title: Expert Syst. Appl. doi: 10.1016/j.eswa.2022.118910 – volume: 2022 start-page: 1 year: 2022 ident: 2451_CR11 publication-title: International Transactions on Electrical Energy Systems doi: 10.1155/2022/1870136 – ident: 2451_CR13 doi: 10.1109/tpwrd.2021.3104746 – ident: 2451_CR3 – ident: 2451_CR1 – ident: 2451_CR8 doi: 10.1109/NPSC49263.2020.9331843 – ident: 2451_CR15 doi: 10.1109/ACCESS.2023.3268763 – ident: 2451_CR6 doi: 10.15598/aeee.v14i5.1733 – ident: 2451_CR10 doi: 10.3390/en15186521 – volume: 207 start-page: 107834 year: 2022 ident: 2451_CR12 publication-title: Electric Power Systems Research doi: 10.1016/j.epsr.2022.107834 – year: 2023 ident: 2451_CR5 doi: 10.6084/m9.figshare.c.6628553.v1 – ident: 2451_CR2 doi: 10.1109/EPE51172.2020.9269171 |
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| Title | A Data Set of Signals from an Antenna for Detection of Partial Discharges in Overhead Insulated Power Line |
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