| L360钢在H2S/CO2环境中腐蚀的预测 |
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| 引用本文： | 赵景茂,魏辉荣,张娇娇,熊金平,唐聿明,左禹. L360钢在H2S/CO2环境中腐蚀的预测[J]. 腐蚀科学与防护技术, 2012, 0(2): 163-166 |
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| 作者姓名： | 赵景茂 魏辉荣 张娇娇 熊金平 唐聿明 左禹 |
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| 作者单位： | 北京化工大学材料科学与工程学院 |
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| 摘 要： | 运用BP人工神经网络技术建立了预测L360钢在H2S/CO2环境中腐蚀的模型,神经网络拓扑结构为5-4-1,网络模型训练成功以后,应用它预测L360钢在H2S/CO2中的腐蚀速度.结果表明,人工神经网络模型预测的结果与实验数据相当符合,误差在14%以内.由此可见,BP神经网络模型可以作为预测H2S/CO2环境致集输管线腐蚀速率的工具.
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| 关 键 词： | L360钢 H2S/CO2腐蚀 BP人工神经网络 腐蚀速率 |
Prediction of Corrosion Rate of L360 Steel in H2S/CO2 Environment |
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| ZHAO Jing-mao,WEI Hui-rong,ZHANG Jiao-jiao,XIONG Jin-ping,TANG Yu-ming,ZUO Yu. Prediction of Corrosion Rate of L360 Steel in H2S/CO2 Environment[J]. Corrosion Science and Protection Technology, 2012, 0(2): 163-166 |
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| Authors: | ZHAO Jing-mao WEI Hui-rong ZHANG Jiao-jiao XIONG Jin-ping TANG Yu-ming ZUO Yu |
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| Affiliation: | College of Materials Science and Engineering,Beijing University of Chemical Technology,Beijing 100029 |
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| Abstract: | An BP（back-propagation） aritifical neueal network（ANN） model for the predicting of the corrosion rate of L360 steel in H2S/CO2 environment was established,neural network architecture is 5-4-1.After the successive training,the model could be applied to predict the corrosion rate of L360 steel in H2S/CO2 environment.The forecast results from the network model are in good agreement with the experimental data,the comparative error is less than 14%.Application of BP aritifical neural network to predict the corrosion rate of gathering and transport pipeline in H2S/CO2 environment is feasible. |
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| Keywords: | L360 steel H2S/CO2 corrosion BP artifical neural network corrosion rate |
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