DocumentCode
3293617
Title
Fault Locating of Grounding Grids Based on Ant colony Optimizing Elman Neural Network
Author
Zhipeng, Yi ; Minfang, Peng ; Hao, He ; Xianfeng, Liu
Author_Institution
Hunan Univ. of Electr. Eng., Changsha, China
fYear
2012
fDate
July 31 2012-Aug. 2 2012
Firstpage
406
Lastpage
409
Abstract
In order to improve the accuracy and efficiency of the fault location of grounding grids, a new method combing ant colony algorithm (ACA) with Elman neural network is proposed. The method contrasts the voltages of the test points when the grounding grids is normal or not. The simulation results showes that the method can save time and improve accuracy.
Keywords
ant colony optimisation; earthing; fault location; power grids; recurrent neural nets; ACA; Elman neural network; ant colony algorithm; fault location; grounding grids; Biological neural networks; Conductors; Fault diagnosis; Grounding; Training; Vectors; Elman neural network; ant colony algorithm; fault locating; grounding grids;
fLanguage
English
Publisher
ieee
Conference_Titel
Digital Manufacturing and Automation (ICDMA), 2012 Third International Conference on
Conference_Location
GuiLin
Print_ISBN
978-1-4673-2217-1
Type
conf
DOI
10.1109/ICDMA.2012.97
Filename
6298338
Link To Document