Lifetime prediction for organic coating under alternating hydrostatic pressure by artificial neural network
文献类型：期刊论文
| 作者 | Tian, Wenliang ; Meng, Fandi ; Liu, Li ; Li, Ying ; Wang, Fuhui |
| 刊名 | SCIENTIFIC REPORTS
 |
| 出版日期 | 2017-01-17 |
| 卷号 | 7页码:- |
| ISSN号 | 2045-2322 |
| 通讯作者 | Liu, L (reprint author), Chinese Acad Sci, Inst Met Res, Wencui Rd 62, Shenyang 110016, Peoples R China. |
| 中文摘要 | 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. |
| 学科主题 | Multidisciplinary Sciences |
| 收录类别 | SCI |
| 资助信息 | National Natural Science Fund of China [51271187, 51622106]; National Basic Research Program of China [2014CB643303, 2014CB643301] |
| 语种 | 英语 |
| 公开日期 | 2017-08-17 |
| 源URL | [http://ir.imr.ac.cn/handle/321006/78336]  |
| 专题 | 金属研究所_中国科学院金属研究所 |
| 推荐引用方式 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.(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):-. |
入库方式： OAI收割
来源：金属研究所
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