| 基于自适应神经网络技术的钠泵诊断 |
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| 引用本文： | 冯俊婷,王桂增,徐銤,刘国发.基于自适应神经网络技术的钠泵诊断[J].核动力工程,2003,24(5):462-466. |
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| 作者姓名： | 冯俊婷 王桂增 徐銤 刘国发 |
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| 作者单位： | 1. 中国原子能科学研究院,北京,102413
2. 清华大学自动化系,北京,100084 |
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| 摘 要： | 在径向基函数网络的基础上，应用自适应算法使故障诊断方法具有自适应性：在对中国实验快堆(CEFR)钠泵的故障仿真实验中．该方法能够较好地识别出故障。为了提高识别的准确率，本文在自适应径向基函数网络的基础上对其自适应算法进行了一定的改进，使故障诊断的准确率有所提高。
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| 关 键 词： | 自适应 径向基函数网络 故障诊断 钠泵 实验快堆 |
| 文章编号： | 0258-0926(2003)05-0462-05 |
| 修稿时间： | 2002年8月19日 |
Fault Diagnosis for Sodium Pump Based on Self-Adaptive Neural Networks |
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| FENG Jun-ting,WANG Gui-zeng,XU Mi,LIU Guo-fa.Fault Diagnosis for Sodium Pump Based on Self-Adaptive Neural Networks[J].Nuclear Power Engineering,2003,24(5):462-466. |
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| Authors: | FENG Jun-ting WANG Gui-zeng XU Mi LIU Guo-fa |
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| Affiliation: | FENG Jun-ting1,WANG Gui-zeng2,XU Mi1,LIU Guo-fa1 |
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| Abstract: | Based on the basic radial basis function networks (RBF), an adaptive algorithm is incorpo-rated to get the self-adaptive capability in fault diagnosis. This method is applied to fault diagnosis for so-dium pump for China Experiment Fast Reactor (CEFR).Simulation results have shown the better capability for detecting and isolating faults. In order to increase isolating veracity, based on adaptive RBF networks, an adaptive algorithm is improved. |
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| Keywords: | Adaptive Radial basis function networks Fault diagnosis Sodium pump Experiment Fast reactor |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
