文献详情
Kohonen Neural Network Classification for Failure Process of Metallic Organic Coating in Corrosion Environment
文献类型期刊
作者Xu, Yuanming[1];Ran, Junshuang[2];Chen, Hao[3]
机构
通讯作者Ran, JS (reprint author), Beihang Univ, Sch Aeronaut Sci & Engn, Beijing 100191, Peoples R China.
来源信息年:2017  卷:7  期:4  
期刊信息METALS影响因子和分区  ISSN:2075-4701
关键词coating; corrosion; EIS; Kohonen neural network; classification
摘要A deeper insight into the changing states of corrosion during certain exposure circumstances has been investigated by applying Kohonen networks. The Kohonen network has been trained by four sets of samples and tested using another sample. All the sample data were collected during accelerated corrosion experiments and the network took the changing rate of impedance of each cycle as an input. Compared with traditional classification, the Kohonen artificial network method classifies corrosion process into five sub-processes which is a refinement of three typical corrosion processes. The two newly defined sub-processes of corrosion-namely, pre-middle stage and post-middle stage-were introduced. The EIS data and macro-morphology for both sub-processes were analyzed through accelerated experiments. The classification results of the Kohonen artificial network are highly consistent with the predictions based on impedance magnitude at low frequency, which illustrates that the Kohonen network classification is an effective method for predicting the failure cycles of polymer coatings.
收录情况SCIE(WOS:000404051600041)  
所属部门航空科学与工程学院
DOI10.3390/met7040147
学科材料科学:综合;冶金工程
人气指数18
浏览次数18
基金National High Technology Research and Development Program of China (863 Program); Aeronautical Science Foundation of China [2014ZE21009]; Foundation of the Key Laboratory of Beijing, China
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