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Extracting Characteristics from Corrosion Surface of Carbon Steel Based on WPT and SVD

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Recent Advances in Computer Science and Information Engineering

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 125))

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Abstract

In order to study the early corrosion behavior of marine carbon steel in electrolyzed ballast water, a novel approach for extracting feature of the corrosion morphology images was proposed using waveletpacket transform (WPT) and singularity value decomposition (SVD). The waveletpacket transform and the singularity value decomposition arithmetic were introduced. The characteristic parameters p1and p2 were defined based on the singular value characteristic vector. The intrinsic relations between the characteristic parameters and the corrosion behavior of marine carbon steel were discussed. It has been shown that the characteristic parameters can reveal the early corrosion behavior of marine carbon steel. The parameter p1 reflects the corrosion rate of carbon steel, which is coincident with the evolution of corrosion weight loss, the larger characteristic parameter p1, the larger corrosion weight loss and the higher corrosion rate. The parameter p2 reflects the size and quantity of pitting corrosion, the larger characteristic parameter p2, the larger and few pitting corrosion. Therefore the corrosion morphology can be identified by the characteristic parameters p1and p2 .

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Correspondence to Li Guo-bin .

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© 2012 Springer-Verlag GmbH Berlin Heidelberg

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Guo-bin, L., Ting-ju, L. (2012). Extracting Characteristics from Corrosion Surface of Carbon Steel Based on WPT and SVD. In: Qian, Z., Cao, L., Su, W., Wang, T., Yang, H. (eds) Recent Advances in Computer Science and Information Engineering. Lecture Notes in Electrical Engineering, vol 125. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25789-6_16

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  • DOI: https://doi.org/10.1007/978-3-642-25789-6_16

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-25788-9

  • Online ISBN: 978-3-642-25789-6

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