| 基于DPCA-BP的故障诊断方法 |
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| 引用本文： | 刘喜梅,钟丽丽,步妮.基于DPCA-BP的故障诊断方法[J].青岛科技大学学报,2012(5):546-550. |
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| 作者姓名： | 刘喜梅 钟丽丽 步妮 |
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| 作者单位： | 青岛科技大学自动化与电子工程学院 |
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| 基金项目： | 青岛市应用基础研究计划项目(2011) |
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| 摘 要： | 针对动态主元分析(DPCA)在故障识别方面的缺点,引入了BP神经网络,将DP-CA与BP神经网络相结合,增强了对故障的辨识能力。该方法通过对各测量变量的自相关性分析,来降低动态主元分析中增广矩阵的维数,从而降低了分析过程的计算量。最后,将DPCA-BP应用于田纳西-伊斯曼过程的故障诊断中,验证了所提出方法的有效性。
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| 关 键 词： | DPCA 故障诊断 BP网络 |
Fault Diagnosis Method Based on DPCA-BP |
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| LIU Xi-mei,ZHONG Li-li,BU Ni.Fault Diagnosis Method Based on DPCA-BP[J].Journal of Qingdao University of Science and Technology:Natutral Science Edition,2012(5):546-550. |
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| Authors: | LIU Xi-mei ZHONG Li-li BU Ni |
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| Affiliation: | (College of Automation and Electronic Engineering,Qingdao University of Science and Technology,Qingdao 266042,China) |
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| Abstract: | BP neural network is introduced to improve the dynamic principal component(DPCA)analysis in fault identification.By analyzing the autocorrelation of the measured variables,the dimension of the augmented matrix in dynamic principal component analysis is reduced,and the difficulty of calculation is decreased.Finally,the proposed DPCA-BP method is verified to be effective on the fault diagnosis by the application in the Tennessee-Eastman process. |
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| Keywords: | DPCA fault diagnosis BP neural network |
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