<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>This paper firstly proposes distributed fiber optic sensing technology based on big data technology and physics, distributed fiber optic sensing technology includes distributed fiber optic sensing technology based on interference type and distributed fiber optic sensing technology based on the scattering principle. Then investigated the demand for remote monitoring of distributed fiber optic sensing systems and the demand for large sensing networks in the Internet of Things and designed a long-distance distributed fiber optic sensing-based intelligent monitoring system. Finally, the vibration acceleration signal of the metal shell when partial discharge occurs is collected, and the high-frequency components in the vibration acceleration signal are used to diagnose and analyze the discharging faults caused by the metal particles of GIL. The results show that: when the rated current is loaded on the GIL, the main frequency distribution of the vibration acceleration signal on the surface of the metal shell is from 0 to 1 kHz, and the percentage of the signal energy in this frequency band is greater than 99% of the total energy in the range of 0 to 20 kHz. In the frequency range of 1 kHz to 20 kHz, the percentage of the signal energy in the total energy does not exceed 1%, and there is almost no high-frequency vibration acceleration signal. This study and the combination of these two technologies is a great contribution to the further development of each, but also more favorable for application in work and life.</p>
</abstract>

This paper firstly proposes distributed fiber optic sensing technology based on big data technology and physics, distributed fiber optic sensing technology includes distributed fiber optic sensing technology based on interference type and distributed fiber optic sensing technology based on the scattering principle. Then investigated the demand for remote monitoring of distributed fiber optic sensing systems and the demand for large sensing networks in the Internet of Things and designed a long-distance distributed fiber optic sensing-based intelligent monitoring system. Finally, the vibration acceleration signal of the metal shell when partial discharge occurs is collected, and the high-frequency components in the vibration acceleration signal are used to diagnose and analyze the discharging faults caused by the metal particles of GIL. The results show that: when the rated current is loaded on the GIL, the main frequency distribution of the vibration acceleration signal on the surface of the metal shell is from 0 to 1 kHz, and the percentage of the signal energy in this frequency band is greater than 99% of the total energy in the range of 0 to 20 kHz. In the frequency range of 1 kHz to 20 kHz, the percentage of the signal energy in the total energy does not exceed 1%, and there is almost no high-frequency vibration acceleration signal. This study and the combination of these two technologies is a great contribution to the further development of each, but also more favorable for application in work and life.

Distributed optical fiber sensing technology in operation status monitoring of GIL equipment

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

This paper firstly proposes distributed fiber optic sensing technology based on big data technology and physics, distributed fiber optic sensing technology...

Distributed optical fiber sensing technology in operation status monitoring of GIL equipment

Online veröffentlicht: 02. Sept. 2023

Seitenbereich: -

Eingereicht: 29. Sept. 2022

Akzeptiert: 13. März 2022

DOI: https://doi.org/10.2478/amns.2023.2.00274

Schlüsselwörter
Big data technology, Physics, Fiber optic sensing technology, Intelligent detection system, GIL equipment

© 2023 Wenjiao Du et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Distributed optical fiber sensing technology in operation status monitoring of GIL equipment

Online veröffentlicht: 02. Sept. 2023

Seitenbereich: -

Eingereicht: 29. Sept. 2022

Akzeptiert: 13. März 2022

DOI: https://doi.org/10.2478/amns.2023.2.00274

SchlüsselwörterBig data technology, Physics, Fiber optic sensing technology, Intelligent detection system, GIL equipment

© 2023 Wenjiao Du et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
Big data technology, Physics, Fiber optic sensing technology, Intelligent detection system, GIL equipment