Fractal characteristic of pits distribution on 304 stainless steel corroded surface and its application in corrosion diagnosis

被引：15

作者：

Liang Chenghao ^{[1
]}

Zhang Wei

机构：

[1] Dalian Maritime Univ, Electmech & Mat Engn Coll, Dalian 116026, Peoples R China

[2] Zhejiang Univ Technol, Coll Mech Engn, Hangzhou 310032, Peoples R China

来源：

JOURNAL OF WUHAN UNIVERSITY OF TECHNOLOGY-MATERIALS SCIENCE EDITION | 2007年 / 22卷 / 03期

关键词：

304 stainless steel; pits distribution; fractal; neural network; diagnosis; MOLTEN-CARBONATE; COPPER CORROSION; BEHAVIOR; INHIBITION; STEELS; ENVIRONMENT; MEDIA;

D O I：

10.1007/s11595-006-3389-3

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

Electrochemical techniques and fractal theory were employed to study the corrosion behaviors and pits distribution characteristics on the corroded surfaces of 304 stainless steel exposed in FeCl3 solution. Fractal features of pits distribution over the corroded surfaces were observed and described by the fractal dimension. A 5-8-2 back-propagation (BP) artificial neural network model for the diagnoses of the pitting corrosion rate and pits deepness of 304 stainless steel under various conditions was developed by considering the fractal dimension as a key parameter for describing the pitting corrosion characteristics. The predicted results are well in agreement with the experimental data of pitting corrosion rate and pit deepness. The max relative errors between their experimental and simulation data are 6.69% and 4.62%, respectively.

引用

页码：389 / 393

页数：5

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