| 基于RBF模型的埋地管道外腐蚀速率预测 |
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| 引用本文： | 梁昌晶,管恩东.基于RBF模型的埋地管道外腐蚀速率预测[J].油气储运,2022(2):233-240. |
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| 作者姓名： | 梁昌晶 管恩东 |
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| 作者单位： | 河北华北石油港华勘察规划设计有限公司;中国石油天然气集团有限公司辽河油田公司高升采油厂 |
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| 摘 要： | 为克服埋地管道土壤腐蚀因素之间具有模糊性、随机性、交互性及传统方法预测精度较低等缺陷,以某现场埋地管道腐蚀埋片数据为基础,选择10个影响因素为输入参数,以外腐蚀速率为输出参数,采用径向基函数(Radial Basis Function,RBF)神经网络模型,对数据样本进行训练、验证、测试,建立外腐蚀速率预测模型,并通过...
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| 关 键 词： | 径向基 埋地管道 外腐蚀 Sobol敏感度 土壤电阻率 |
External corrosion rate prediction of buried pipeline based on RBF model |
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| LIANG Changjing,GUAN Endong.External corrosion rate prediction of buried pipeline based on RBF model[J].Oil & Gas Storage and Transportation,2022(2):233-240. |
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| Authors: | LIANG Changjing GUAN Endong |
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| Institution: | (Hebei Huabei Petroleum GangHua Survey Planning&Design Co.Ltd.;Gaosheng Oil Production Plant,CNPC Liaohe Oilfield Company) |
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| Abstract: | In order to overcome the shortcomings of fuzziness,randomness and interaction between the soil corrosion factors of buried pipeline,as well as the low accuracy of prediction with the traditional methods,a prediction model of external corrosion rate was established with 10 influencing factors as the input,and the external corrosion rate as the output based on the field data of corrosion coupons of a buried pipeline.Thereby,the data samples were trained,verified and tested using the Radial Basis Function(RBF)neural network mode,and the key parameters affecting the corrosion were identified through Sobol sensitivity analysis.The results show that the mean square error is 0.00099 when 10-35-1 type RBF model is iterated to step 2273,and the correlation coefficients of the training,validation and testing stages are 0.9707,0.9813 and 0.9901 respectively.Compared with BP,MLR and SVM models,the average relative error of RBF neural network model is 2.07%,indicating that RBF neural network model has some advantages in terms of the external corrosion rate prediction of buried pipeline.The soil resistivity has the maximum effect on the external corrosion rate.Moreover,the soil resistivity,pH value,and Cl-content significantly interact with other factors,which should be paid much more attention.Generally,the established model can be effectively applied to the external corrosion rate prediction of pipeline,and the results could provide theoretical basis and reference for pipeline integrity management. |
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| Keywords: | radial basis buried pipeline external corrosion Sobol sensitivity soil resistivity |
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