基于动态PCA的核动力装置传感器故障检测 |
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引用本文: | 宋梅村,蔡琦.基于动态PCA的核动力装置传感器故障检测[J].武汉水运工程学院学报,2012(6):1184-1187,1191. |
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作者姓名: | 宋梅村 蔡琦 |
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作者单位: | 海军工程大学船舶与动力学院,武汉430033 |
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摘 要: | 针对变工况过程中传统主元分析方法的模型不适应问题,通过稳定性因子分析,剔除过渡过程数据,并用模糊聚类方法将不同稳态工况进行分类,利用动态主元模型方法根据工况类型建立不同的主元模型,并将该方法用于核动力装置传感器的故障检测,结果表明该方法能够适应变工况情况下的传感器故障检测,减少了故障的误检,并提高了检测灵敏度.
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关 键 词: | 主元分析 变工况过程 稳定性因子 模糊聚类 故障检测 |
Sensor Fault Detection for Nuclear Power Plant Based on Dynamic Principal Component Analysis |
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Authors: | SONG Meicun CAI Qi |
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Institution: | (College of Power Engineering ,Naval Univ. of Engineering, Wuhan 430033, China) |
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Abstract: | As to the maladjustment of model of traditional principal component analysis in changing condition process, different principal component models have been built by dynamic principal compo- nent analysis according to condition type, through stability factor analysis to eliminate the changing process data and condition classification of different steady conditions with the fuzzy-clustering meth- od. This method is applied to sensor fault detection for nuclear power plant . The result shows that it is fit for sensor fault detection in changing condition process, it reduces the chances of detection mis- takes and it improves the detection sensitivity. |
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Keywords: | principal component analysis changing condition process stability factor fuzzy-clustering fault detection |
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