Application of single hidden layer fuzzy recurrent wavelet neural network to multi-physical parameter monitoring and on-line analysis of high voltage power equipment

Shiling Zhang; Song Wei; Yin Hua

doi:10.1117/12.2668982

28 March 2023 Application of single hidden layer fuzzy recurrent wavelet neural network to multi-physical parameter monitoring and on-line analysis of high voltage power equipment

Shiling Zhang, Song Wei, Yin Hua

Author Affiliations +

Proceedings Volume 12566, Fifth International Conference on Computer Information Science and Artificial Intelligence (CISAI 2022); 125663Y (2023) https://doi.org/10.1117/12.2668982
Event: Fifth International Conference on Computer Information Science and Artificial Intelligence (CISAI 2022), 2022, Chongqing, China

Abstract

The sensor for the SF6 characteristic decomposition gas based on the non dispersive infrared technology(NDIR) is designed. The system adopts the single light source and the dual wavelength optical structure, and further develops the optical sensor detection system for SF6 decomposition products. The system adopts single light source and dual wavelength structure to eliminate the unstable factors of the measurement system and has the high measurement accuracy. On the basis of effectively obtaining the time series of SF6 decomposition product volume fraction, the SLFRWNN(1, N) system model is applied to fit and predict it, and the high-precision fitting of gas volume fraction and prediction and analysis of gas concentration in wide area time domain are realized. The combination of the NDIR technology and system SLFRWNN(1, N) model provides novel method for the rapid measurement and prediction of SF6 decomposition gas in gas insulated switch-gear.

Citation Download Citation

Shiling Zhang, Song Wei, and Yin Hua "Application of single hidden layer fuzzy recurrent wavelet neural network to multi-physical parameter monitoring and on-line analysis of high voltage power equipment", Proc. SPIE 12566, Fifth International Conference on Computer Information Science and Artificial Intelligence (CISAI 2022), 125663Y (28 March 2023); https://doi.org/10.1117/12.2668982

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