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2013 (Vol. 6, Issue: 07)
Article Information:

Study on Iron Bacteria Induced Corrosion Based on Electrochemical Noise and RBF Neural Network

Men Hong, Zhang Li Hua, Li Xiujie, Zhao Xiao and Zhang Jing
Corresponding Author:  Men Hong 

Key words:  Frequency-domain analysis, iron bacteria, radial basis function, stainless steel c304, time-domain analysis, ,
Vol. 6 , (07): 1309-1315
Submitted Accepted Published
November 24, 2012 January 14, 2013 July 05, 2013
Abstract:

In this study, a study on iron bacteria induced corrosion based on Electrochemical Noise (EN) and Radial Basis Function (RBF) neural network is presented. Through the iron bacteria's corrosion compared test on C304 stainless steel, we use time domain analysis, frequency domain analysis and RBF neural network to analysis the EN data received by electrochemical workstation. Compared the results obtained by the three methods, we can conclude that the RBF neural network can recognized the iron bacteria induced corrosion types, with more advance than the traditional analysis methods.
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  Cite this Reference:
Men Hong, Zhang Li Hua, Li Xiujie, Zhao Xiao and Zhang Jing, 2013. Study on Iron Bacteria Induced Corrosion Based on Electrochemical Noise and RBF Neural Network.  Research Journal of Applied Sciences, Engineering and Technology, 6(07): 1309-1315.
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ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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