Dataset of phase-resolved images of internal, corona, and surface partial discharges in electrical generators
This article presents the data collection process for the classification of partial discharges in electrical generators using PNG format images. The data were collected through field measurements on over 40 generators in various locations in Colombia, in addition to utilizing a partial discharge sim...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2024-02-01
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| Series: | Data in Brief |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352340923010223 |
| _version_ | 1797317146628325376 |
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| author | Juan David Zorrilla Henao Alejandro Segura Alejandro Tenorio Harold José Diaz Alejandro Paz |
| author_facet | Juan David Zorrilla Henao Alejandro Segura Alejandro Tenorio Harold José Diaz Alejandro Paz |
| author_sort | Juan David Zorrilla Henao |
| collection | DOAJ |
| description | This article presents the data collection process for the classification of partial discharges in electrical generators using PNG format images. The data were collected through field measurements on over 40 generators in various locations in Colombia, in addition to utilizing a partial discharge simulator provided by Omicron Energy.Throughout the collection process, special attention was given to the accuracy and coherence of the images, avoiding deformations and distortions that could impact the nature of partial discharges. Emphasis was placed on achieving high resolution in phase-resolved patterns (PRPD) to effectively correlate them with the adjacent physical phenomenon. The analysis focused on classifying the images according to the type of partial discharge, identifying them as internal, surface, or corona discharges. The obtained pulse patterns are represented in RGB color, which aids in assessing the repeatability of pulses across their distribution.These data hold potential for the development of pattern classification software for generator monitoring systems. They enable the training and validation of classification algorithms, simplifying the automated detection and analysis of partial discharges in electrical generators. Their applicability extends beyond the electrical industry and can be valuable in other fields requiring complex signal and pattern analysis.The article highlights the rigorous data collection process and precise analysis conducted to obtain a valuable set of PNG format images for partial discharge classification. These data have significant potential in advancing pattern classification software, driving progress in the monitoring and analysis of electrical generators. |
| first_indexed | 2024-03-08T03:30:39Z |
| format | Article |
| id | doaj.art-c2c161b7bbcb4fb1bcf6c4c78818959a |
| institution | Directory Open Access Journal |
| issn | 2352-3409 |
| language | English |
| last_indexed | 2024-03-08T03:30:39Z |
| publishDate | 2024-02-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Data in Brief |
| spelling | doaj.art-c2c161b7bbcb4fb1bcf6c4c78818959a2024-02-11T05:10:53ZengElsevierData in Brief2352-34092024-02-0152109992Dataset of phase-resolved images of internal, corona, and surface partial discharges in electrical generatorsJuan David Zorrilla Henao0Alejandro Segura1Alejandro Tenorio2Harold José Diaz3Alejandro Paz4School of Electrical and Electronic Engineering (IEEE), Faculty of Engineering, Universidad del Valle; Corresponding author.School of Electrical and Electronic Engineering (IEEE), Faculty of Engineering, Universidad del ValleSchool of Electrical and Electronic Engineering (IEEE), Faculty of Engineering, Universidad del ValleSchool of Electrical and Electronic Engineering (IEEE), Faculty of Engineering, Universidad del ValleFaculty of Engineering, Santiago de Cali UniversityThis article presents the data collection process for the classification of partial discharges in electrical generators using PNG format images. The data were collected through field measurements on over 40 generators in various locations in Colombia, in addition to utilizing a partial discharge simulator provided by Omicron Energy.Throughout the collection process, special attention was given to the accuracy and coherence of the images, avoiding deformations and distortions that could impact the nature of partial discharges. Emphasis was placed on achieving high resolution in phase-resolved patterns (PRPD) to effectively correlate them with the adjacent physical phenomenon. The analysis focused on classifying the images according to the type of partial discharge, identifying them as internal, surface, or corona discharges. The obtained pulse patterns are represented in RGB color, which aids in assessing the repeatability of pulses across their distribution.These data hold potential for the development of pattern classification software for generator monitoring systems. They enable the training and validation of classification algorithms, simplifying the automated detection and analysis of partial discharges in electrical generators. Their applicability extends beyond the electrical industry and can be valuable in other fields requiring complex signal and pattern analysis.The article highlights the rigorous data collection process and precise analysis conducted to obtain a valuable set of PNG format images for partial discharge classification. These data have significant potential in advancing pattern classification software, driving progress in the monitoring and analysis of electrical generators.http://www.sciencedirect.com/science/article/pii/S2352340923010223Partial dischargeGeneratorInternalCoronaSurfaceData augmentation |
| spellingShingle | Juan David Zorrilla Henao Alejandro Segura Alejandro Tenorio Harold José Diaz Alejandro Paz Dataset of phase-resolved images of internal, corona, and surface partial discharges in electrical generators Data in Brief Partial discharge Generator Internal Corona Surface Data augmentation |
| title | Dataset of phase-resolved images of internal, corona, and surface partial discharges in electrical generators |
| title_full | Dataset of phase-resolved images of internal, corona, and surface partial discharges in electrical generators |
| title_fullStr | Dataset of phase-resolved images of internal, corona, and surface partial discharges in electrical generators |
| title_full_unstemmed | Dataset of phase-resolved images of internal, corona, and surface partial discharges in electrical generators |
| title_short | Dataset of phase-resolved images of internal, corona, and surface partial discharges in electrical generators |
| title_sort | dataset of phase resolved images of internal corona and surface partial discharges in electrical generators |
| topic | Partial discharge Generator Internal Corona Surface Data augmentation |
| url | http://www.sciencedirect.com/science/article/pii/S2352340923010223 |
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