基于RBF神经网络的2024铝合金酸性 盐雾腐蚀实验预测
TG146.2+1; 选用飞机结构材料2024铝合金进行不同条件下的酸性盐雾实验,设定盐雾实验的pH值分别为2、3、5,盐雾浓度分别为25 g/L、50 g/L、75 g/L,腐蚀时间分别为24 h、48 h、72 h.将径向基函数神经网络(radial basis function neural networks,RBF)与正交实验设计相结合,选取不同的实验条件组作为神经网络的学习样本集,并通过极差分析对正交实验结果进行分析.结果表明:采用RBF与正交实验设计相结合的方法,能够较准确地预测任意实验条件下的腐蚀速率,减少实验次数,提高预测精度;把正交组和顶点补充组同时作为学习样本集的预测结果要...
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| Published in | 航空材料学报 Vol. 39; no. 4; pp. 32 - 39 |
|---|---|
| Main Authors | , , |
| Format | Journal Article |
| Language | Chinese |
| Published |
中国民航大学航空工程学院,天津,300300%中国民航大学中欧航空工程师学院,天津,300300
01.08.2019
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1005-5053 |
| DOI | 10.11868/j.issn.1005-5053.2018.000114 |
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| Abstract | TG146.2+1; 选用飞机结构材料2024铝合金进行不同条件下的酸性盐雾实验,设定盐雾实验的pH值分别为2、3、5,盐雾浓度分别为25 g/L、50 g/L、75 g/L,腐蚀时间分别为24 h、48 h、72 h.将径向基函数神经网络(radial basis function neural networks,RBF)与正交实验设计相结合,选取不同的实验条件组作为神经网络的学习样本集,并通过极差分析对正交实验结果进行分析.结果表明:采用RBF与正交实验设计相结合的方法,能够较准确地预测任意实验条件下的腐蚀速率,减少实验次数,提高预测精度;把正交组和顶点补充组同时作为学习样本集的预测结果要优于单单只有正交组作为学习样本集的预测结果.极差分析结果表明,对2024铝合金单位面积的质量损耗影响最大的因素是溶液的pH值,其次是盐雾浓度,腐蚀时间的影响最小. |
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| AbstractList | TG146.2+1; 选用飞机结构材料2024铝合金进行不同条件下的酸性盐雾实验,设定盐雾实验的pH值分别为2、3、5,盐雾浓度分别为25 g/L、50 g/L、75 g/L,腐蚀时间分别为24 h、48 h、72 h.将径向基函数神经网络(radial basis function neural networks,RBF)与正交实验设计相结合,选取不同的实验条件组作为神经网络的学习样本集,并通过极差分析对正交实验结果进行分析.结果表明:采用RBF与正交实验设计相结合的方法,能够较准确地预测任意实验条件下的腐蚀速率,减少实验次数,提高预测精度;把正交组和顶点补充组同时作为学习样本集的预测结果要优于单单只有正交组作为学习样本集的预测结果.极差分析结果表明,对2024铝合金单位面积的质量损耗影响最大的因素是溶液的pH值,其次是盐雾浓度,腐蚀时间的影响最小. |
| Author | 贾宝惠 方艺斌 王毅强 |
| AuthorAffiliation | 中国民航大学航空工程学院,天津,300300%中国民航大学中欧航空工程师学院,天津,300300 |
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| Author_FL | JIA Baohui FANG Yibin WANG Yiqiang |
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| Copyright | Copyright © Wanfang Data Co. Ltd. All Rights Reserved. |
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| DocumentTitle_FL | Prediction of acid salt spray corrosion experiment of 2024 aluminum alloy based on RBF neural network |
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| Keywords | 径向基函数神经网络 酸性盐雾实验 正交实验 铝合金 |
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| Publisher | 中国民航大学航空工程学院,天津,300300%中国民航大学中欧航空工程师学院,天津,300300 |
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| Title | 基于RBF神经网络的2024铝合金酸性 盐雾腐蚀实验预测 |
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