DocumentCode :
2281128
Title :
A new approach to determine subtransient parameters of synchronous machine using wavelet transform and artificial neuron network
Author :
Xusheng, Wu ; Zhenyu, Shi ; Xiaoyi, Jiang
Author_Institution :
Coll. of Electr. & Inf. Eng., Naval Univ. of Eng., China
fYear :
2011
fDate :
20-23 Aug. 2011
Firstpage :
1
Lastpage :
3
Abstract :
Based on the wavelet transform and artificial neuron network, a new method is presented to determine parameters of synchronous machine from sudden line-to-line short-circuit test. An appropriate wavelet function is chosen to analyze the sudden line-to-line short-circuit transient current and the DC and fundamental component of the transient short-circuit currents are obtained by the wavelet transform. Compared with the traditional methods, the analysis using wavelet transform is more effective. Thus, the precise transient parameters and aperiodic component time constant are estimated by the artificial neuron network. At last, the simulation of sudden line-to-line short-circuit are carried out in a three-phase synchronous machine. The simulation results show that the method developed in this paper is valid.
Keywords :
electric machine analysis computing; neural nets; short-circuit currents; synchronous machines; wavelet transforms; aperiodic component time constant; artificial neuron network; line-to-line short-circuit test; line-to-line short-circuit transient current; three-phase synchronous machine; wavelet transform; Current measurement; Educational institutions; Neurons; Synchronous machines; Transient analysis; Wavelet transforms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrical Machines and Systems (ICEMS), 2011 International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4577-1044-5
Type :
conf
DOI :
10.1109/ICEMS.2011.6073850
Filename :
6073850
Link To Document :
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