Journal of Liaoning Petrochemical University

Journal of Liaoning Petrochemical University ›› 2012, Vol. 32 ›› Issue (4): 52-54.DOI: 10.3696/j.issn.1672-6952.2012.04.014

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Prediction of Safe Shutdown Time of Oil Pipeline Based on RBF Neural Network

 

GAO Yan-bo1， MA Gui-yang1*，LIU Hong-yu2，YAO Yao1，WANG Lei1，DAI Kan-liang1
  

  1. 1.College of Petroleum Engineering，Liaoning Shihua University，Fushun Liaoning 113001，P.R .China；2. Domestic Division, China Petroleum Pipeline Bureau, Langfang Hebei 065000, P.R.China
  • Received:2012-05-07 Published:2012-12-20 Online:2017-07-06

基于RBF神经网络的输油管道安全停输时间预测

高艳波１，马贵阳１＊，刘宏宇２，姚　尧１，王　雷１，代堪亮１   

  1. １．辽宁石油化工大学石油天然气工程学院，辽宁抚顺１１３００１；
    ２．中国石油天然气管道局国内事业部，河北廊坊０６５０００
  • 作者简介:高艳波（１９８７－），女，吉林松原市，在读硕士。

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Abstract:  

Considering the difficulty in the estimation of safe shutdown time of oil pipeline due to the complex safe shutdown of submarine oil pipeline influencing factors, the radial basis function neural network model was proposed for predicting safe shutdown time of submarine oil pipeline and the various influence factors on safe shutdown of oil pipeline were analyzed. The model was validated on the basis of actual data and the network was trained and the accuracy was verified. The results show that the fitting and simulation precision for training and testing samples is 98.40% and 97.33%, respectively. So the safe shutdown time of submarine oil pipeline can be predicted validly, and the important basis of safe transportation of submarine oil pipeline was provided.

Key words:  

摘要：         针对影响海底输油管道停输的因素复杂，难以对管道安全停输时间做出准确判断的问题，提出了海底输油管道安全停输时间预测的径向基函数（ＲＢＦ）神经网络模型，综合考虑了各因素对输油管道安全停输的影响。以实测数据为基础，训练网络并验证了模型的预测准确性。研究结果表明，径向基函数神经网络预测模型对训练样本的拟合精度和对验证样本的仿真精度分别达到９８．４０％和９７．３３％，可对海底输油管道安全停输时间进行有效预测，为海底输油管道的安全输送提供重要依据。

关键词: 　径向基函数, 　安全停输, 　海底输油管道, 　预测

Cite this article

GAO Yan-bo， MA Gui-yang，LIU Hong-yu，YAO Yao，WANG Lei，DAI Kan-liang.  

Prediction of Safe Shutdown Time of Oil Pipeline Based on RBF Neural Network
[J]. Journal of Liaoning Petrochemical University, 2012, 32(4): 52-54.

高艳波，马贵阳，刘宏宇，等. 基于RBF神经网络的输油管道安全停输时间预测[J]. 辽宁石油化工大学学报, 2012, 32(4): 52-54.

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