Quantitative Analysis for SF6 and its Compositions in GIS
2012 ◽
Vol 562-564
◽
pp. 1336-1339
Keyword(s):
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.
2013 ◽
Vol 756-759
◽
pp. 3804-3808
2013 ◽
Vol 427-429
◽
pp. 1048-1051
Keyword(s):
2013 ◽
Vol 448-453
◽
pp. 3605-3609
2020 ◽
Vol 20
(1)
◽
pp. 53-64