|本期目录/Table of Contents|

[1]靳文博 李新战 肖荣鸽 赵 军 李 凯.海洋环境下3C钢腐蚀速度多元非线性回归模型的建立及验证[J].中国海上油气,2019,31(04):171-176.[doi:10.11935/j.issn.1673-1506.2019.04.023]
 JIN Wenbo LI Xinzhan XIAO Rongge ZHAO Jun LI Kai.Establishment and verification of multivariate nonlinear regression model for corrosion rate of 3C steel in marine environment[J].China Offshore Oil and Gas,2019,31(04):171-176.[doi:10.11935/j.issn.1673-1506.2019.04.023]
点击复制

海洋环境下3C钢腐蚀速度多元非线性回归模型的建立及验证()

《中国海上油气》[ISSN:1673-1506/CN:11-5339/TE]

卷:
第31卷
期数:
2019年04期
页码:
171-176
栏目:
海洋工程
出版日期:
2019-07-25

文章信息/Info

Title:
Establishment and verification of multivariate nonlinear regression model for corrosion rate of 3C steel in marine environment
文章编号:
1673-1506(2019)04-0171-06
作者:
靳文博12 李新战3 肖荣鸽12 赵 军12 李 凯12
(1. 西安石油大学石油工程学院 陕西西安 710065; 2. 陕西省油气田特种增产技术重点实验室 陕西西安 710065; 3. 中石油管道有限责任公司西气东输分公司甘陕管理处 陕西西安 710021)
Author(s):
JIN Wenbo12 LI Xinzhan3 XIAO Rongge12 ZHAO Jun12 LI Kai12
(1. College of Petroleum Engineering, Xi'an Shiyou University, Xi'an, Shaanxi 710065, China; 2. Shaanxi Key Laboratory of Advanced Stimulation Technology for Oil & Gas Reservoirs, Xi'an, Shaanxi 710065, China; 3. Gan-Shan Management Office, West-East
关键词:
海洋环境因素 钢材腐蚀速度 多元非线性模型 线性回归模型 误差分析
Keywords:
marine environmental factors corrosion rate of steel multivariate nonlinear model linear regression model error analysis
分类号:
TG172.5
DOI:
10.11935/j.issn.1673-1506.2019.04.023
文献标志码:
A
摘要:
通过分析海水环境因素对钢材腐蚀速度的影响,采用多元非线性分析方法建立了计算3C钢腐蚀速度的多元非线性数学模型,并将其计算结果与线性回归模型的计算结果及实验结果进行了对比。结果表明:在考虑各自变量相互作用的情况下,本文建立的多元非线性模型的平均相对误差为8.249%,均方误差为1.607,其精度高于未考虑各自变量相互作用的非线性模型精度; 而线性模型的平均相对误差为12.406%,均方误差为4.169,其精度低于非线性模型; 采用三次多项式来描述腐蚀速度与温度和盐度之间的关系是合理的。本文研究结果可为海洋环境下3C钢腐蚀速度的预测提供有益借鉴。
Abstract:
By analyzing the influence of seawater environmental factors on steel corrosion rate, a multivariate non-linear mathematical model for calculating corrosion rate of 3C steel was established by using multivariate non-linear analysis method, and the calculated results were compared with those of linear regression model and experimental results. The results show that the average relative error and mean square error of the multivariate nonlinear model in this paper are 8.249% and 1.607 respectively when considering the interaction of the variables, and the precision is higher than that of the nonlinear model without considering the interaction among them. The average relative error and mean square error of the linear model are 12.406% and 4.169 respectively, and the precision of the linear model is lower than that of the nonlinear model. It is reasonable to use cubic polynomial to describe the relationship of corrosion rate with temperature and salinity and corrosion rate. The results of this study can provide useful reference for predicting corrosion rate of 3C steel in marine environment.

参考文献/References:

[1] 王红红,刘国恒.中国海油海底管道事故统计及分析[J].中国海上油气,2017,29(5):157-160.DOI:10.11935/j.issn.1673-1506.2017.05.022. WANG Honghong,LIU Guoheng.Statistics and analysis of subsea pipeline accidents of CNOOC[J].China Offshore Oil and Gas,2017,29(5):157-160.DOI:10.11935/j.issn.1673-1506.2017.05.022. [2] 胡丽华,常炜,张雷,等.X65钢和3Cr钢作为海底管道用钢抗CO2腐蚀性能研究[J].中国海上油气,2011,23(2):131-134. HU Lihua,CHANG Wei,ZHANG Lei,et al.Research on the CO2 corrosion resistance of X65 and 3Cr steels applied to subsea pipeline[J].China Offshore Oil and Gas,2011,23(2):131-134. [3] 刘学庆.海洋环境工程钢材腐蚀行为与预测模型的研究[D].北京:中国科学院大学,2004. LIU Xueqing.Investigation on the corrosion behavior and corrosion prediction model of engineering steels used in marine environment[D].Beijing:University of Chinese Academy of Sciences,2004. [4] 胡舸.海底管线腐蚀检测与腐蚀预测的研究[D].重庆:重庆大学,2007. HU Ge.Study on submarine pipeline corrosion detection and corrosion prediction[D].Chongqing:Chongqing university,2007. [5] 张彦军,韩文礼,白玉洁,等.海洋钢结构飞溅区防腐蚀技术现状[J].全面腐蚀控制,2012,26(5):8-10. ZHANG Yanjun,HAN Wenli,BAI Yujie,et al.Anti-corrosion technology of steel structure for splash zone[J].Total Corrosion Control,2012,26(5):8-10. [6] 翟秀云.基于PSO-RBFNN的3C钢在海水环境中的腐蚀速率预测[J].腐蚀与防护,2014,35(11):1127-1130,1155. ZHAI Xiuyun.Prediction of corrosion rate of 3C steel in sea water environment based on PSO-RBFNN[J].Corrosion and Protection,2014,35(11):1127-1130,1155. [7] LEE T S,MONEY K L.Difficulties in developing tests to simulate corrosion in Marine environments[J].Materials Performance,1984,23(8):28-33. [8] 雒娅楠.海洋环境中金属材料现场电化学检测及冲刷腐蚀研究[D].天津:天津大学,2006. LUO Yanan.In field electrochemical detection and erosion-corrosion investigation of metallic materials in marine environment[D].Tianjin:Tianjin University,2006. [9] 宋伟伟,董彩常,张波.人工神经网络在我国海水腐蚀中的应用[J].腐蚀与防护,2012,33(8):668-671,694. SONG Weiwei,DONG Caichang,ZHANG Bo.Application of artificial neural network to metal corrosion in seawater[J].Corrosion and Protection,2012,33(8):668-671,694. [10] 孔涛,王佳,钟莲.组合人工神经网络模型预测海水腐蚀速度的研究[J].腐蚀科学与防护技术,2008,20(1):58-61. KONG Tao,WANG Jia,ZHONG Lian.Prediction of marine corrosion using a combined artificial neural network model[J].Corrosion Science and Protection Technology,2008,20(1):58-61. [11] 李晓峰,王海涛,邵良杉.基于人工神经网络的碳钢、低合金钢腐蚀预测[J].西安建筑科技大学学报(自然科学版),2008,40(6):885-888. LI Xiaofeng,WANG Haitao,SHAO Liangshan.Corrosion forecast of carbon steel and low alloy steel based on the artificial neural network[J].Journal of Xi'an University of Architecture & Technology(Natural Science Edition),2008,40(6):885-888. [12] 孔德英,宋诗哲.人工神经网络技术探讨碳钢、低合金钢的实海腐蚀规律[J].中国腐蚀与防护学报,1998,18(4):289-296. KONG Deying,SONG Shizhe.Analysis of corrosion data for Carbon steel and low-alloy steels seawater by artificial neural network[J].Journal of Chinese Society for Corrosion and Protection,1998,18(4):289-296. [13] 侯健,王伟伟,邓春龙.海水环境因素与材料腐蚀相关性研究[J].装备环境工程,2010,7(6):167-170. HOU Jian,WANG Weiwei,DENG Chunlong.Study on relation between environmental factors and corrosion in seawater[J].Equipment Environmental Engineering,2010,7(6):167-170. [14] 张明禄,张建国,王本成,等.试油层非线性产量预测模型研究[J].西南石油大学学报(自然科学版),2015,37(6):99-104. ZHANG Minglu,ZHANG Jianguo,WANG Bencheng,et al.Study on the prediction model of oil testing formation non-linear productivity[J].Journal of Southwest Petroleum University(Science & Technology Edition),2015,37(6):99-104. [15] 郝天轩,柳猛.基于多元非线性回归理论的煤层瓦斯含量预测[J].煤炭技术,2014,33(9):1-3. HAO Tianxuan,LIU Meng.Prediction of coal seam gas content based on multivariate nonlinear regression[J].Coal Technology,2014,33(9):1-3. [16] 赵永兴,杜应吉,刘方琼,等.基于多元非线性分析的粉煤灰混凝土碳化模型研究[J].混凝土,2017(3):74-77,81. ZHAO Yongxing,DU Yingji,LIU Fangqiong,et al.Study on carbonation model for fly ash concrete based on multivariate nonlinear analysis[J].Concrete,2017(3):74-77,81. [17] 李松,杜应吉.基于多元非线性分析的混凝土强度预测模型[J].混凝土,2016(3):44-46,55. LI Song,DU Yingji.Model of concrete strength prediction based on multivariate nonlinear analysis[J].Concrete,2016(3):44-46,55. [18] 刘学庆,王佳,王胜年,等.海水中3C钢腐蚀速度影响因素的灰关联分析[J].腐蚀科学与防护技术,2005,17(增刊1):494-496. LIU Xueqing,WANG Jia,WANG Shengnian,et al.Evaluation of seawater effects on corrosion rates of 3C steel by grey interrelation analysis[J].Corrosion Science and Protection Technology,2005,17(S1):494-496.

相似文献/References:

备注/Memo

备注/Memo:
*国家自然科学基金青年项目“复杂地层条件下自升式钻井平台桩靴基础穿刺破坏机理及评估方法研究(编号:51609201)”部分研究成果。 第一作者简介: 靳文博,男,博士,讲师,主要从事油气管道流动安全保障技术研究。地址:陕西省西安市雁塔区电子二路18号西安石油大学(邮编:710065)。E-mail:jinwenbo725@163.com。
更新日期/Last Update: 1900-01-01