Abstract Details
155 / 2024-04-15 09:45:43
On-line vacuum degree detection of vacuum circuit breaker based on laser-induced breakdown spectroscopy combined with WTD-RF
Laser-induced plasma,Vacuum interrupter,Machine learning,On-line monitoring
Draft Accepted
In the field of high-voltage switchgear, the vacuum circuit breaker has the advantages of strong breaking capacity, compact structure, and environmental protection. However, on-line monitoring of vacuum degree of vacuum interrupter remains a challenge. The vacuum detection method based on laser-induced plasma breakdown spectroscopy (LIBS) technology is expected to achieve safe and reliable online monitoring of vacuum degree in vacuum interrupters.
Therefore, a model combined with wavelet threshold denoising and random forest regression (WTD-RF) is proposed to measure the vacuum degree of vacuum interrupter. Firstly, WTD is used to reduce the background noise and improve the spectral signal-to-noise ratio. Then, the relationship of spectral line integral intensity and the vacuum degree is trained by RF.
The prediction results of vacuum degree are compared by multiple machine learning models. It is found that the proposed model in this paper has better generalization ability and higher accuracy obtained by the comprehensive evaluation matrix.
The study shows that the WTD-RF improve the detection ability of vacuum degree and can be the suitable method for monitoring the LIBS-based vacuum degree detection of vacuum interrupter.
Therefore, a model combined with wavelet threshold denoising and random forest regression (WTD-RF) is proposed to measure the vacuum degree of vacuum interrupter. Firstly, WTD is used to reduce the background noise and improve the spectral signal-to-noise ratio. Then, the relationship of spectral line integral intensity and the vacuum degree is trained by RF.
The prediction results of vacuum degree are compared by multiple machine learning models. It is found that the proposed model in this paper has better generalization ability and higher accuracy obtained by the comprehensive evaluation matrix.
The study shows that the WTD-RF improve the detection ability of vacuum degree and can be the suitable method for monitoring the LIBS-based vacuum degree detection of vacuum interrupter.
Important Date
-
Conference Date
Nov 10
2024
toNov 13
2024
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Nov 11 2024
Draft paper submission deadline
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Nov 19 2024
Registration deadline
Sponsored By
Xi’an Jiaotong Universit
Contact Information
Previous Conferences
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2022-11-24 Bangladesh Dhaka
2022 International Conference on Energy and Power Engineering -
2019-03-14 Bangladesh
2019 International Conference on Energy and Power Engineering
