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

Abstract

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.

Keywords

304 stainless steel / pits distribution / fractal / neural network / diagnosis

References

[1] López D., Sánchez C., Toro A. Corrosion-erosion Behavior of TiN-Coated Stainless Steels in Aqueous Slurries [J]. Wear, 2005, 258(1–4): 684-692.

[2] Migahed M. A., Aly R. O., Al-Sabagh A. M. Impact of Gammaray-pre-irradiation on the Efficiency of Corrosion Inhibition of Some Novel Polymeric Surfactants [J]. Corros. Sci., 2004, 46(10): 2 503-2 516.

[3] Zhang J. X., Yuan J., Qiao Y., . The Corrosion and Passivation of SS304 Stainless Steel under Square Wave Electric Field [J]. Mater. Chem. Phys., 2003, 79(1): 43-48.

[4] Abdallah M. Rhodanine Azosulpha Drugs as Corrosion Inhibitors for Corrosion of 304 Stainless Steel in Hydrochloric Acid Solution [J]. Corros. Sci., 2002, 44(4): 717-728.

[5] Cond A., García I., Damhorenea J. J. Pitting Corrosion of 304 Stainless Steel After Laser Surface Melting in Argon and Nitrogen Atmospheres [J]. Corros. Sci., 2001, 43(5): 817-828.

[6] Otmacic H., Stupnišek-Lisac E. Copper Corrosion Inhibitors in Near Neutral Media [J]. Electrochim. Acta, 2003, 48(8): 985-991.

[7] Lindbergh G., Zhu B. Corrosion Behaviour of High Aluminium Steels in Molten Carbonate in an Anode Gas Environment [J]. Electrochim. Acta, 2001, 46(8): 1 131-1 140.

[8] Zhu B., Lindbergh G. Corrosion Behaviour of High-chromium Ferritic Steels in Molten Carbonate in Cathode Environment [J]. Electrochim. Acta, 2001, 46(17): 2 593-2 604.

[9] Quartarone G., Bellomi T. Zingales A. Inhibition of Copper Corrosion by Isatin in Aerated 0.5 M H₂SO₄ [J]. Corros. Sci., 2003, 45(4): 715-733.

[10] Hsu W. W., Yang C. C., Huang C. A., . Investigation on the Corrosion Behavior of Ti-6Al-4V Implant Alloy by Electrochemical Techniques [J]. Mater. Chem. Phys., 2004, 86(2–3): 269-278.

[11] Şahin M., Bilgiç S., Yılmaz H. The Inhibition Effects of Some Cyclic Nitrogen Compounds on the Corrosion of the Steel in NaCl Mediums [J]. Appl. Surf. Sci., 2002, 195(1–4): 1-7.

[12] Park H., Szpunar J. A. The Role of Texture and Morphology in Optimizing the Corrosion Resistance of Zinc-based Electrogalvanized Coatings [J]. Corros. Sci., 1998, 40(4–5): 525-545.

[13] Itzhak D., Dinstein I., Zilberberg T. Pitting Corrosion Evaluation by Computer Image Processing [J]. Corros. Sci., 1981, 21: 17-22.

[14] Yan Y. H., Wang H. M., Li S. P. Biomedical Image Processing using FCM Algorithm Based on the Wavelet Transform [J]. Journal of Wuhan University of Technology-Mater. Sci. Ed., 2004, 19(3): 18-20.

[15] Mandelbrot B. B. The Fractal Geometry of Nature[M], 1982. Freeman: San Francisco. 1-100.

[16] Lee C. K., Ho D. S., Yu C. C., . Fractal Analysis of Temporal Variation of Air Pollutant Concentration by Box Counting [J]. Environ. Model. Softw., 2003, 18(3): 243-251.

[17] Yang Z. Y., Zhou A. N. Fractal Characteristics and Fractal Dimension Measurement on Broken Surface of Aluminum Electric Porcelain [J]. Journal of Wuhan University of Technology-Mater. Sci. Ed., 2005, 20(1): 37-41.