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Evaluation of Corrosion Residual Life Prediction Methods for Metal Pipelines

摘要:The analysis of the basic characteristics of various research methods is highly needed to predict the residual life of the pipeline accurately, help managers understand the operational risks, and provide a reference for developing pipeline transportation and maintenance inspection plans and anti-corrosion measures. Based on a comprehensive investigation of the existing research on the residual life of the pipeline, this paper finds that the current mainstream life prediction method, based on historical statistical data, has the shortcomings of inconsistent modeling methods, inconsistent basic data, and a lack of comparative evaluation among methods. Moreover, considering the in-depth study of BP neural network modeling, grey theory modeling, time series modeling, and exponential smoothing modeling, optimal prediction models using different methods based on the same historical data are established. These optimal modeling methods are discussed, and the feasible modeling path for the accurate prediction of the pipeline's residual life is given by comparing the prediction accuracy of each model. In addition, the findings serve as a guide for developing an anti-corrosion strategy by highlighting the contribution of the prediction results of the residual life to pipeline decision-making. By comparison, it is found that the accuracy of the four prediction models is as follows: the grey theory prediction model, the exponential smoothing prediction model, the BP neural network prediction model, and the time series prediction model, from high to low, respectively.

关键字:corroded pipeline; residual life prediction; anti-corrosion; BP neural network; inspection data

ISSN号:1996-1944

卷、期、页:卷: 15期: 16

发表日期:2022-08-01

影响因子:3.623400

期刊分区(SCI为中科院分区):三区

收录情况:SCIE(科学引文索引网络版),EI(工程索引)

发表期刊名称:MATERIALS

参与作者:曾春雷,胡兴乔,赵云,费凡

通讯作者:都胜杰

第一作者:左丽丽

论文类型:期刊论文

论文概要:左丽丽,曾春雷,胡兴乔,都胜杰,赵云,费凡,Evaluation of Corrosion Residual Life Prediction Methods for Metal Pipelines,MATERIALS,2022,卷: 15期: 16

论文题目:Evaluation of Corrosion Residual Life Prediction Methods for Metal Pipelines

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