| 基于模糊最小-最大神经网络的输油管道泄漏故障诊断方法 |
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| 引用本文： | 刘金海,冯健.基于模糊最小-最大神经网络的输油管道泄漏故障诊断方法[J].南京航空航天大学学报,2011(Z1). |
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| 作者姓名： | 刘金海 冯健 |
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| 作者单位： | 东北大学信息科学与工程学院; |
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| 基金项目： | 中央高校基本科研业务(N100304007)资助项目; 国家高技术研究发展计划(“八六三”计划)(2009AA04Z127)资助项目; 国家自然科学基金(50977008)资助项目; 新世纪优秀人才支持计划(NCET-08-0101)资助项目 |
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| 摘 要： | 提出一种基于模糊最小-最大神经网络的输油管道泄漏故障诊断方法。该方法将管道压力特征作为模糊最小-最大神经网络的输入,通过模糊最小-最大神经网络的输出判断管道是否发生泄漏,并且针对实测数据含有噪声和测量误差的情况,设计一种可以有效处理实测数据的隐含节点函数。通过对管道试验系统实测数据的验证,本文方法可以有效检测管道泄漏故障。
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| 关 键 词： | 故障诊断 模糊最小-最大神经网络 管道运输 实测数据 |
Diagnosis for Oil Pipeline Based on Fuzzy Min-Max Neural Network |
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| Liu Jinhai,Feng Jian.Diagnosis for Oil Pipeline Based on Fuzzy Min-Max Neural Network[J].Journal of Nanjing University of Aeronautics & Astronautics,2011(Z1). |
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| Authors: | Liu Jinhai Feng Jian |
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| Institution: | Liu Jinhai,Feng Jian(School of Information Science and Engineering,Northeastern University,Shenyang,110004,China) |
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| Abstract: | A new diagnosis method for oil pipeline based on fuzzy min-max neural network(MMNN) is proposed,using the pressure characteristics of pipeline as input parameters.By the output of fuzzy MMUN,the states of pipeline can be determined.Moreover,a new membership function of fuzzy MMNN for real data is designed,which can deal with data containing noise and measurement error.The method is validated by the simulation of liquid test system. |
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| Keywords: | fault diagnosis fuzzy min-max neural network pipeline transport real data |
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