Title :
Earth parameter and equivalent resistivity estimation using ANN
Author :
Lee, P. ; Ji, P.S. ; Lim, J.Y. ; Kim, S.S. ; Ozdemir, A. ; Singh, C.
Author_Institution :
Dept. of Electr. Eng., Chung-Buk Nat. Univ., Cheongju, South Korea
Abstract :
Earth equipments are essential to protect human or other equipment from abnormal conditions. Earth resistance and potential must be restricted within low value to protect humans and equipment. An estimation algorithm of earth parameters and equivalent resistivity is introduced to calculate reliable earth resistance in this research. The proposed algorithm is based on the relationship between apparent resistances and earth parameters. The proposed algorithm, which approximates the non-linear characteristics of earth by using artificial neural network (ANN), estimates the earth parameters and equivalent resistivity. The effectiveness of the proposed method is verified with case studies.
Keywords :
accident prevention; earthing; electrical engineering computing; neural nets; parameter estimation; ANN; Earth parameter estimation; artificial neural network; earth resistance reliability; equivalent resistivity estimation; human protection; nonlinear characteristics; Artificial neural networks; Conductivity; Earth; Neurons; Optimization methods; Organizing; Parameter estimation; Pattern classification; Testing; Training data;
Conference_Titel :
Power Engineering Society General Meeting, 2005. IEEE
Print_ISBN :
0-7803-9157-8
DOI :
10.1109/PES.2005.1489485