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Lifetime prediction for organic coating under alternating hydrostatic pressure by artificial neural network
Tian, Wenliang; Meng, Fandi; Liu, Li; Li, Ying; Wang, Fuhui; Liu, L (reprint author), Chinese Acad Sci, Inst Met Res, Wencui Rd 62, Shenyang 110016, Peoples R China.
2017-01-17
Source PublicationSCIENTIFIC REPORTS
ISSN2045-2322
Volume7Pages:-
AbstractA concept for prediction of organic coatings, based on the alternating hydrostatic pressure (AHP) accelerated tests, has been presented. An AHP accelerated test with different pressure values has been employed to evaluate coating degradation. And a back-propagation artificial neural network (BP-ANN) has been established to predict the service property and the service lifetime of coatings. The pressure value (P), immersion time (t) and service property (impedance modulus vertical bar Z vertical bar) are utilized as the parameters of the network. The average accuracies of the predicted service property and immersion time by the established network are 98.6% and 84.8%, respectively. The combination of accelerated test and prediction method by BP-ANN is promising to evaluate and predict coating property used in deep sea.; A concept for prediction of organic coatings, based on the alternating hydrostatic pressure (AHP) accelerated tests, has been presented. An AHP accelerated test with different pressure values has been employed to evaluate coating degradation. And a back-propagation artificial neural network (BP-ANN) has been established to predict the service property and the service lifetime of coatings. The pressure value (P), immersion time (t) and service property (impedance modulus vertical bar Z vertical bar) are utilized as the parameters of the network. The average accuracies of the predicted service property and immersion time by the established network are 98.6% and 84.8%, respectively. The combination of accelerated test and prediction method by BP-ANN is promising to evaluate and predict coating property used in deep sea.
description.department[tian, wenliang ; meng, fandi ; liu, li ; li, ying ; wang, fuhui] chinese acad sci, inst met res, wencui rd 62, shenyang 110016, peoples r china
Subject AreaMultidisciplinary Sciences
Funding OrganizationNational Natural Science Fund of China [51271187, 51622106]; National Basic Research Program of China [2014CB643303, 2014CB643301]
Indexed BySCI
Language英语
Document Type期刊论文
Identifierhttp://ir.imr.ac.cn/handle/321006/78336
Collection中国科学院金属研究所
Corresponding AuthorLiu, L (reprint author), Chinese Acad Sci, Inst Met Res, Wencui Rd 62, Shenyang 110016, Peoples R China.
Recommended Citation
GB/T 7714
Tian, Wenliang,Meng, Fandi,Liu, Li,et al. Lifetime prediction for organic coating under alternating hydrostatic pressure by artificial neural network[J]. SCIENTIFIC REPORTS,2017,7:-.
APA Tian, Wenliang,Meng, Fandi,Liu, Li,Li, Ying,Wang, Fuhui,&Liu, L .(2017).Lifetime prediction for organic coating under alternating hydrostatic pressure by artificial neural network.SCIENTIFIC REPORTS,7,-.
MLA Tian, Wenliang,et al."Lifetime prediction for organic coating under alternating hydrostatic pressure by artificial neural network".SCIENTIFIC REPORTS 7(2017):-.
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