Procedure for characterization of HF, VHF and UHF analisers used in high voltage installations diagnosis
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| 著者: | , , , , , |
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| フォーマット: | artículo original |
| 状態: | Versión publicada |
| 出版日付: | 2021 |
| その他の書誌記述: | PD monitoring in electrical grids and high voltage installations to evaluate the insulation condition of different assets is a very topical issue, however, there are no criteria or procedures to evaluate the technical performances of these measuring and diagnosis systems. Cable systems are monitored with HFCT type sensors as each sensor has a measurement range of several kilometres. In GIS installations, invasive sensors of the UHF type are widely used, as they present high sensitivity to detect small PD despite their measuring range is a few meters and for power transformers the capacitance of its bushing is used, as a coupling capacitor coupled to a measuring impedance. Although there is apparently no universal solution to solve the same problem “detection of the electrical insulation defect”, the capabilities of the different measuring techniques conventional, HF, VHF and UHF techniques are not well known. This paper presents a test procedure using a single-phase high-voltage test bench (20 kV) composed of a GIS and a cable system that allows conducting tests of characterization of measuring systems working with conventional, HFCT, VHF or UHF sensors. Partial discharges are generated by a set of specially designed reference test cells or by a reference generator of PD pulses used as a calibrator. |
| 国: | Portal de Revistas TEC |
| 機関: | Instituto Tecnológico de Costa Rica |
| Repositorio: | Portal de Revistas TEC |
| 言語: | Español |
| OAI Identifier: | oai:ojs.pkp.sfu.ca:article/6009 |
| オンライン･アクセス: | https://revistas.tec.ac.cr/index.php/tec_marcha/article/view/6009 |
| キーワード: | PD measurements PD sensitivity HFCT type sensor VHF and UHF sensors electrical noise automatic recognition of defects artificial intelligence Medidas de DP Sensibilidad de DP sensor de tipo HFCT sensores de tipo VHF y UHF ruido eléctrico reconocimiento automático de defectos Inteligencia artificial |