Detection of trace CF4 in C4F7N‐insulated gas‐insulated metal‐enclosed switchgear: Cascading specific chemical reactions with photoacoustic spectroscopy
Abstract CF4 is a major decomposition product of the insulating gas in C4F7N‐insulated gas‐insulated metal‐enclosed switchgear (GIS) during partial discharge or overheating faults. Its detection is essential for effective online monitoring and fault diagnosis of GIS. However, the application of phot...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2025-06-01
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| Series: | High Voltage |
| Online Access: | https://doi.org/10.1049/hve2.70049 |
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| Summary: | Abstract CF4 is a major decomposition product of the insulating gas in C4F7N‐insulated gas‐insulated metal‐enclosed switchgear (GIS) during partial discharge or overheating faults. Its detection is essential for effective online monitoring and fault diagnosis of GIS. However, the application of photoacoustic spectroscopy for CF4 detection is hampered by significant cross‐interference from the background C4F7N gas. In this paper, quantum chemical calculations revealed that C4F7N hydrolyses to form perfluoroisobutyrate and ammonia under base catalysis, exhibiting a low reaction energy barrier and high Gibbs free energy change, indicating ease of initiation and substantial reaction extent. This chemical specificity, unlike the stable CF4 which does not undergo such a reaction, enables selective purification of the gas to be detected through this hydrolysis reaction. Leveraging this insight, an experimental system was constructed that cascades chemical absorption purification with photoacoustic spectroscopy detection. This system effectively mitigates the cross‐interference of C4F7N in CF4 detection by selectively absorbing C4F7N with over 95% efficiency through a base‐catalysed nucleophilic hydrolysis reaction. This enabled the precise detection of trace amounts of CF4 against a substantial background of C4F7N with a detection limit reaching 14.79 μL/L. This advancement offers support for the online monitoring and fault diagnosis of eco‐friendly GIS. |
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| ISSN: | 2397-7264 |