摘要
为精准预测埋地管道腐蚀剩余寿命,解决埋地管道腐蚀剩余寿命预测中内外腐蚀耦合机制考量不足的问题,选取231个不同规格和材质的天然气输送管道管段为样本,综合内外腐蚀因素,采用PLS与LOOCV筛选出13项核心输入指标,构建RBFNN预测模型。模型以8∶2比例划分训练集与测试集,并在MATLAB平台进行训练验证,并与其他模型对比。结果表明,该模型在18个训练周期内收敛,所建模型对训练样本的拟合精度相对误差控制在±5%,对独立预测样本的仿真检验精度达95.86%,预测精度较高;此外,MSE、RMSE等指标优于ABC-GM、GJO-RBF等模型,揭示了内外腐蚀因子非线性耦合规律。RBFNN模型具有较强的泛化与鲁棒性,可为管道完整性管理、检验周期优化及风险防控提供可靠支撑,并明确了关键影响因子及防控方向。
To accurately predict the remaining life of buried pipelines and address the issue of insufficient consideration of the coupling mechanism between internal and external corrosion in the prediction of the remaining life of buried pipelines,231 pipeline sections of different specifications and materials for natural gas transportation were selected as samples.Considering both internal and external corrosion factors,PLS and LOOCV were used to screen out 13 core input indicators,then an RBFNN prediction model was constructed.The model is divided into a training set and a test set in a 8:2 ratio,and is trained and validated on the MATLAB platform,and compared with other models.The results show that the model converged within 18 training cycles.The relative error of the model's fitting accuracy for the training samples was controlled within±5%,and the simulation verification accuracy for independent prediction samples reached 95.86%.The prediction accuracy was relatively high.In addition,the indicators such as MSE and RMSE were superior to those of models like ABC-GM and GJO-RBF,and they revealed the nonlinear coupling rules of internal and external corrosion factors.This indicates that the RBFNN model has strong generalization and robustness,which can provide reliable support for pipeline integrity management,optimization of inspection cycles,and risk prevention and control,and clarifies the key influencing factors and prevention directions.
作者
方学锋
姚尧
邹慧慧
刘英坤
张伯君
FANG Xuefeng;YAO Yao;ZOU Huihui;LIU Yingkun;ZHANG Bojun(Nanjing Boiler and Pressure Vessel Inspection Institute,Nanjing 210019,China)
出处
《焊管》
2025年第12期36-41,共6页
Welded Pipe and Tube
基金
国家市场监督管理总局科技计划项目“多源干扰下城镇燃气钢质管道环境腐蚀监测控制技术研究及工程示范”(项目编号2023MK159)
江苏省市场监督管理局科技项目“多源干扰下埋地钢质管道杂散电流检测技术研究”(项目编号KJ2024066)
南京市市场监督管理局科技项目“动态直流杂散电流干扰评价及缓解措施优化设计研究”(项目编号Kj2023011)
关键词
埋地输气管道
管道内外腐蚀
剩余寿命预测
径向基函数
buried gas transmission pipeline
internal and external corrosion
prediction of remaining life
radial basis function
