I tiakina i:
| Ngā kaituhi matua: | , , , , , , |
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| Hōputu: | Recurso digital |
| Reo: | |
| I whakaputaina: |
Zenodo
2026
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| Ngā marau: | |
| Urunga tuihono: | https://doi.org/10.3897/jucs.145075 |
| Ngā Tūtohu: |
Tāpirihia he Tūtohu
Kāore He Tūtohu, Me noho koe te mea tuatahi ki te tūtohu i tēnei pūkete!
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Rārangi ihirangi:
- Power utilities demand large volumes of data used in power distribution networks. Among them are parameters representing possible technical failures, such as network's short circuit current and voltage sag. Specialists find these parameters and detect technical failures. However, this process can become time-consuming. Thus, this article proposes an ontology called OntoFreya, which classifies voltage, current, or any electric metric, following the definitions of the regulatory agencies and reducing the time spent on this task. A series of 4402 axioms, 132 classes, and 40 data properties comprises OntoFreya. The ontology automatically inferred classifications for four hundred readings from energy samples, validating OntoFreya across three scenarios. The first and second scenarios classified current in amperes, and the third classified voltage in per-unit system (pu). The scenarios showed that OntoFreya automates the classification of electric metrics, reducing specialists' time in detecting technical failures in a distribution network.