| 基于高斯混合模型和变量重构组合法的故障诊断与分离 |
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| 引用本文： | 李元,孙健.基于高斯混合模型和变量重构组合法的故障诊断与分离[J].南京航空航天大学学报,2011(Z1). |
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| 作者姓名： | 李元 孙健 |
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| 作者单位： | 沈阳化工大学信息工程学院; |
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| 基金项目： | 国家自然科学基金(60774070.61034006)资助项目; 辽宁省教育厅科学研究基金(20060669.2004D041)资助项目 |
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| 摘 要： | 提出了一种将变量重构与高斯混合模型结合的故障诊断与分离的方法。首先建立过程数据的高斯混合模型,解决了监控过程的测量数据不服从单峰的高斯分布所带来的问题,然后进行故障数据变量重构,估计未知参数并采用最大期望算法来估测均值与协方差矩阵。在此基础上建立统计模型进行故障的诊断与分离。与传统的贡献图分离故障的方法比较,通过田纳西-伊斯曼化工过程进行实验验证,本文提出的高斯混合模型与变量重构相结合对多状态过程进行故障的诊断与分离收到较好效果。
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| 关 键 词： | 控制工程 故障诊断与分离 贡献图 变量重构 高斯混合模型 |
Fault Diagnosis and Isolation Based on Combination Gaussian Mixture Models and Variable Reconstruction |
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| Li Yuan,Sun Jian.Fault Diagnosis and Isolation Based on Combination Gaussian Mixture Models and Variable Reconstruction[J].Journal of Nanjing University of Aeronautics & Astronautics,2011(Z1). |
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| Authors: | Li Yuan Sun Jian |
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| Institution: | Li Yuan,Sun Jian(Department of Information Engineering,Shenyang University of Chemical Technology,Shenyang,110142,China) |
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| Abstract: | A fault diagnosis and isolation approach is presented combining variable reconstruction and Gaussian mixture models(GMMs).Firstly,GMMs for process data are built to overcome the problem that the operating data cannot follow a unimodal Gaussian distribution.Then the variable reconstruction,the estimation of unknown factors and its mean and covariance are completed,as well as the fault diagnosis and isdation.The combination methods are illustrated for a simulated Tennessee-Eastman chemical process(TE) tested ... |
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| Keywords: | control engineering fault diagnosis and isolation contribution plot variable reconstruction Gaussian mixture model |
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