Atmospheric corrosion assessed from corrosion images using fuzzy Kolmogorov-Sinai entropy

IMR OpenIR

	Atmospheric corrosion assessed from corrosion images using fuzzy Kolmogorov-Sinai entropy
	Xia, Da-Hai; Ma, Chao; Song, Shizhe; Jin, Weixian; Behnamian, Yashar; Fan, Hongqiang; Wang, Jihui; Gao, Zhiming; Hu, Wenbin; Fan, HQ (reprint author), Shanghai Univ, Lab Microstruct, Inst Mat, Sch Mat Sci & Engn, Shanghai 200072, Peoples R China.; Xia, DH (reprint author), Tianjin Univ, Tianjin Key Lab Composite & Funct Mat, Sch Mat Sci & Engn, Tianjin 300072, Peoples R China.
	2017-05-15
发表期刊	CORROSION SCIENCE
ISSN	0010-938X
卷号	120 页码:251-256
摘要	Fuzzy Kolmogorov-Sinai (K-S) entropy was used to characterize the irregularity of the spatial information distribution in a corrosion image. The fuzzy K-S entropy was measured for horizontal and vertical orientations of corrosion images of steel samples exposed to a marine atmosphere over 191 days. The fuzzy K-S entropy for horizontal and vertical orientations decreased as the corrosion propagated. A relationship between the fuzzy K-S entropy and the weight loss in the steel sample can be presented with a linear mathematical expression. Fuzzy K-S entropy was found to be a semiquantitative and fast method to quantify atmospheric corrosion. (C) 2017 Elsevier Ltd. All rights reserved.; Fuzzy Kolmogorov-Sinai (K-S) entropy was used to characterize the irregularity of the spatial information distribution in a corrosion image. The fuzzy K-S entropy was measured for horizontal and vertical orientations of corrosion images of steel samples exposed to a marine atmosphere over 191 days. The fuzzy K-S entropy for horizontal and vertical orientations decreased as the corrosion propagated. A relationship between the fuzzy K-S entropy and the weight loss in the steel sample can be presented with a linear mathematical expression. Fuzzy K-S entropy was found to be a semiquantitative and fast method to quantify atmospheric corrosion. (C) 2017 Elsevier Ltd. All rights reserved.
部门归属	[xia, da-hai ; ma, chao ; song, shizhe ; wang, jihui ; gao, zhiming ; hu, wenbin] tianjin univ, tianjin key lab composite & funct mat, sch mat sci & engn, tianjin 300354, peoples r china ; [fan, hongqiang] shanghai univ, lab microstruct, inst mat, sch mat sci & engn, shanghai 200072, peoples r china ; [behnamian, yashar] univ alberta, dept chem & mat engn, edmonton, ab t6g 2v4, canada ; [jin, weixian] cent res inst iron & steel, zhoushan marine corros inst, zhoushan 316000, zhejiang, peoples r china ; [xia, da-hai] chinese acad sci, inst met res, cas key lab nucl mat & safety assessment, shenyang 110016, liaoning, peoples r china
关键词	Carbon Steel Weight Loss Atmospheric Corrosion Kolmogorov-sinai Entropy Image Processing
学科领域	Materials Science, Multidisciplinary ; Metallurgy & Metallurgical Engineering
资助者	Major State Basic Research Development Program (973 Program) [2014CB046805]; National Natural Science Foundation of China [51131007, 51671144, 51471117]; Key Project of Tianjin Natural Science Foundation [13JCZDJC29500]; CAS Key laboratory of Nuclear Materials and Safety Assessment (Institute of Metal Research, Chinese Academy of Sciences, China) [2016NMSAKF02]
收录类别	SCI
语种	英语
文献类型	期刊论文
条目标识符	http://ir.imr.ac.cn/handle/321006/78138
专题	中国科学院金属研究所
通讯作者	Fan, HQ (reprint author), Shanghai Univ, Lab Microstruct, Inst Mat, Sch Mat Sci & Engn, Shanghai 200072, Peoples R China.; Xia, DH (reprint author), Tianjin Univ, Tianjin Key Lab Composite & Funct Mat, Sch Mat Sci & Engn, Tianjin 300072, Peoples R China.
推荐引用方式 GB/T 7714	Xia, Da-Hai,Ma, Chao,Song, Shizhe,et al. Atmospheric corrosion assessed from corrosion images using fuzzy Kolmogorov-Sinai entropy[J]. CORROSION SCIENCE,2017,120:251-256.
APA	Xia, Da-Hai.,Ma, Chao.,Song, Shizhe.,Jin, Weixian.,Behnamian, Yashar.,...&Xia, DH .(2017).Atmospheric corrosion assessed from corrosion images using fuzzy Kolmogorov-Sinai entropy.CORROSION SCIENCE,120,251-256.
MLA	Xia, Da-Hai,et al."Atmospheric corrosion assessed from corrosion images using fuzzy Kolmogorov-Sinai entropy".CORROSION SCIENCE 120(2017):251-256.