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.

Keywords:

Frequency-domain analysis, iron bacteria, radial basis function, stainless steel c304, time-domain analysis,

References

Competing interests

The authors have no competing interests.

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Copyright

The authors have no competing interests.