Author:
Wang Guoqing,Wang Changquan,Shi Lihong
Abstract
The implementation of corrosion detection in submarine pipelines is difficult, and a combined PCA-MLP prediction model is proposed to improve the accuracy of corrosion prediction in submarine pipelines. Firstly, the corrosion rate of a submarine multiphase flow pipeline in the South China Sea is simulated by the De Waard 95 model in the multiphase flow transient simulation software OLGA and compared with the actual corrosion rate; then, according to the corrosion data simulated by OLGA, principal component analysis (PCA) is used to reduce the dimensionality of the corrosion factors in the pipeline, and the multiple linear regression model (MLR), multi-layer perceptron neural network (MLPNN), and radial basis function neural network (RBFNN) were optimized. The PCA-MLPNN model has an average relative error of 3.318%, an average absolute error of 0.0034, a root mean square error of 0.0082, a residual sum of squares of 0.0020, and a coefficient of determination of 0.8609. Compared with five models, including MLR, MLPNN, RBFNN, PCA-MLR, PCA-MLPNN, and PCA-RBFNN, PCA-MLPNN has higher prediction accuracy and better prediction performance. The above results indicate that the combined PCA-MLPNN model has a more reliable application capability in CO2 corrosion prediction of submarine pipelines.
Subject
Atmospheric Science,Environmental Science (miscellaneous)
Reference27 articles.
1. China Submarine Pipeline Engineering Technology Development and Outlook;Oil Gas Storage Transp.,2022
2. An Overview of Maintenance Management Strategies for Corroded Steel Structures in Extreme Marine Environments;Mar. Struct.,2020
3. Veruz, E.G., Miguel, M.M., de Souza, G.F.M., Martins, M.R., Orlowski, R.T.C., Vaz, G.L., and de Barros, L.O. (2022, January 5–10). Reliability-Based Methodology for the Integrity Management of Subsea Oil and Gas Pipelines Subject to Corrosion Degradation. Proceedings of the the 32nd International Ocean and Polar Engineering Conference, Shanghai, China.
4. Prediction of Reliability of the Corroded Pipeline Considering the Randomness of Corrosion Damage and Its Stochastic Growth;Eng. Fail. Anal.,2016
5. Ayello, F., Liu, G., and Zhang, J. (2018). Decision Making Through the Application of Bayesian Network for Internal Corrosion Assessment of Pipelines, American Society of Mechanical Engineers Digital Collection.
Cited by
6 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献