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Journal of Chinese Society for Corrosion and protection  2017, Vol. 37 Issue (5): 444-450    DOI: 10.11902/1005.4537.2017.068
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Correlation Between Corrosion Behavior and Image Information of Q235 Steel Beneath Thin Electrolyte Film
Xinxin ZHANG1,Zhiming GAO1(),Wenbin HU1,Zhipeng WU1,Lianheng HAN1,Lihua LU1,Yan XIU2,Dahai XIA1
1 Tianjin Key Laboratory of Composite and Functional Materials, School of Material Science and Engineering, Tianjin University, Tianjin 300350, China
2 Faculty of Science, Tianjin Chengjian University, Tianjin 300384, China
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Abstract  

The corrosion behavior of Q235 steel beneath electrolyte thin films of 0.01 mol/L NaCl solution was conducted to simulate marine atmospheric corrosion by simultaneous electrochemical measurements and acquisition of corrosion images. The results show that atmospheric corrosion of Q235 steel initiates around pearlites and presents the character of local corrosion which developed to become uniform corrosion afterwards. According to the result of wire beam electrode (WBE) measurement, the mean corrosion potential and the corrosion potential standard deviation decreased, and the anode area enlarged with the exposure time. Analysis of the neural network shows that the content of α-FeOOH in rust layers increased with exposure time, which blocked the process of oxygen diffusion, resulting in the transformation of corrosion mode from local ones to uniform ones. In conclusion, when the electrochemical information shows that the corrosion tends to transform from the local ones to the uniform ones, correspondingly the image information also shows that a protective rust gradually formed with the increasing exposure time. Therefore, the corrosion behavior of Q235 steel presents well correlation with the feature of image information.

Key words:  atmospheric corrosion      Q235 steel      color image processing      rust layer     
Received:  05 May 2017     
Fund: Supported by National Natural Science Foundation of China (51371124, 51671144), Major State Basic Research Development Program of China (2014CB046805) and MOE Project of Humanistic Science Research Younth Fund Project (11YJCZH202)

Cite this article: 

Xinxin ZHANG,Zhiming GAO,Wenbin HU,Zhipeng WU,Lianheng HAN,Lihua LU,Yan XIU,Dahai XIA. Correlation Between Corrosion Behavior and Image Information of Q235 Steel Beneath Thin Electrolyte Film. Journal of Chinese Society for Corrosion and protection, 2017, 37(5): 444-450.

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https://www.jcscp.org/EN/10.11902/1005.4537.2017.068     OR     https://www.jcscp.org/EN/Y2017/V37/I5/444

Fig.1  Surface images of etched Q235 steel after immersion in simulated marine atmospheric environment for 0 min (a), 1 min (b), 5 min (c), 10 min (d), 20 min (e), 30 min (f)
Fig.2  Potential distributions (a~d) and current distributions (e~h) of Q235 steel after immersion in 0.01 molL-1 NaCl solution for 10 min (a, e), 50 h (b, f), 100 h (c, g) and 150 h (d, h)
Fig.3  Variation of mean corrosion potential with time
Fig.4  Variation of corrosion potential standard deviation with time
Fig.5  Changes anode area varying with time
Content of α-FeOOH / % R G B
0 132 102 28
10 135 105 35
20 132 105 23
30 126 101 21
40 135 110 27
50 128 104 26
60 128 106 23
70 130 106 20
80 128 108 17
90 136 112 21
Table 1  Ratios of α-FeOOH (mass fraction / %) and RGB character
Fig.7  Histograms of RGB distribution
Fig.8  Fitting analysis chart of the neural network
Fig.6  Color images of the rust layer in different depths of 0.3~0.5 mm: (a) outer layer, (b, c) middle layer, (d) inner layer
Rust layer In-put (R, G, B) Out-put (α-FeOOH / %)
Fig.6a (116,113,13) 74.88%
Fig.6b (184, 118, 18) 65.87%
Fig.6c (184, 120, 23) 52.96%
Fig.6d (169, 112, 26) 46.63%
Table 2  Analysis results of the rust layer in Fig.6
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