Quantitative Analysis for SF6 and its Compositions in GIS

Hai Lun Wang; Jian Wei Shen

doi:10.4028/www.scientific.net/AMR.562-564.1336

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 562-564Quantitative Analysis for SF6 and its Compositions...

Quantitative Analysis for SF6 and its Compositions in GIS

Abstract:

In this paper, a method for GIS equipment fault diagnosis by the analysis of volume fractions of the derivatives of SF6 gas inside GIS equipment is presented. For the method, based on the differential spectra method, a neural network model and the particle swarm optimization are used for training analysis of infrared spectra, to realize the quantitative analysis of specific derivatives. The experimental results show that the prediction errors obtained by particle swarm optimization training are markedly superior to prediction errors obtained using the traditional method.

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Periodical:

Advanced Materials Research (Volumes 562-564)

Pages:

1336-1339

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.562-564.1336

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Online since:

August 2012

Authors:

Hai Lun Wang, Jian Wei Shen

Keywords:

GIS, Neural Network (NN), Particle Swarm Optimization (PSO), Sulfur Hexafluoride

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References

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