基于深度学习的海底管道外腐蚀剩余强度评估  

Evaluation of residual strength of externally-corroded submarine pipelines based on deep learning

作　　者：谢鹏 刘昊 龚雨晗 倪芃芃 合曼阿澧 XIE Peng;LIU Hao;GONG Yuhan;NI Pengpeng;HEMAN Ali(School of Marine Engineering and Technology,Sun Yat-sen University;Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai);School of Civil Engineering,Sun Yat-sen University)

机构地区：[1]中山大学海洋工程与技术学院 [2]南方海洋科学与工程广东省实验室(珠海) [3]中山大学土木工程学院

出　　处：《油气储运》2021年第6期651-657,共7页Oil & Gas Storage and Transportation

基　　金：国家自然科学基金资助项目“深海管道S型铺设残余变形及屈曲传播机理研究”,52001337;广东省促进经济高质量发展专项资金海洋经济发展项目“3500 m级超深水高压海底管道研制及产业化”,GDOE2019A19;广东省促进经济高质量发展专项资金海洋经济发展项目“抗腐蚀海洋油气管道研制及产业化”,GDOE2020028;广东省重点研发计划“海洋脐带缆研制及产业化项目”,2020B1111040002。

摘　　要：腐蚀是造成海底管道失效的重要原因之一,准确预测海底管道的腐蚀剩余强度是评估海底管道完整性及后续服役能力的关键。基于非线性有限元方法,建立含腐蚀缺陷海底管道剩余强度分析模型,预测管道的剩余强度,并探究了外腐蚀缺陷的深度、长度、宽度对剩余强度的影响。基于深度学习理论建立海底管道剩余强度预测模型,并以有限元分析获得的114组计算结果作为数据集训练深度学习模型,以深度学习模型预测含外腐蚀缺陷海底管道的剩余强度,将模型预测结果与有限元计算结果进行对比。结果表明:深度学习模型计算速度快、预测精度高,验证了基于深度学习的海底管道外腐蚀剩余强度评价方法的可行性与有效性。Corrosion is one of the important causes for submarine pipeline failure.Accurate prediction of the residual strength of corroded submarine pipelines is a key to evaluate the integrity and the subsequent service ability of submarine pipelines.Based on the nonlinear finite element method,a residual strength analysis model was established for the corroded submarine pipelines to predict their residual strength,and the impact of the depth,length and width of the external corrosion on the residual strength of the corroded pipelines was analyzed.Besides,a residual strength prediction model was also established based on the deep learning theory,the residual strength of the corroded submarine pipeline was predicted by the deep learning model that is trained with a dataset comprising 114 groups of calculation results,and the prediction results of the model were compared with the finite element calculation results.The results indicate that the deep learning model has a rapid calculation speed and high prediction precision,which verifies the feasibility and effectiveness of the evaluation method of the residual strength of externally-corroded submarine pipelines based on deep learning.

关 键 词：海底管道 外腐蚀 剩余强度 深度学习 有限元模拟 

分 类 号：TE88[石油与天然气工程—油气储运工程]