| Autor: |
Long Di, Yong Xiao, Feng Hu, Yujian Liang, Jianmin Tan, Yimin You |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
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| Zdroj: |
Advances in Multimedia, Vol 2022 (2022) |
| Druh dokumentu: |
article |
| ISSN: |
1687-5699 |
| DOI: |
10.1155/2022/9136046 |
| Popis: |
In the process of online real-time monitoring of intelligent digital filter high-voltage switchgear, the mechanical state diagnosis of high-voltage circuit breaker is based on fully understanding the mechanical characteristics of each component of circuit breaker. In this paper, K-means clustering algorithm is applied to the mechanical state detection of digital filter high-voltage switchgear. The mechanical state of the digital filter high-voltage switchgear is monitored in real time by using 126 kV GIS. Through fault simulation experiment and mechanical stability experiment, the corresponding changes of characteristics of each mechanical component of circuit breaker in signal waveform and corresponding data changes are found. The experimental results show that this method has good running speed and stability and is more suitable for the real-time monitoring of intelligent digital filter high-voltage switchgear. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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