| 融合FDA-PCMC样本分类的KPCA故障检测新算法 |
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| 引用本文： | 祝志博,宋执环.融合FDA-PCMC样本分类的KPCA故障检测新算法[J].控制与决策,2010,25(4):542-545. |
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| 作者姓名： | 祝志博 宋执环 |
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| 作者单位： | 1. 浙江大学,工业控制技术国家重点实验室,杭州,310027
2. 浙江大学,工业控制研究所,杭州,310027 |
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| 基金项目： | 国家自然科学基金项目(60774067,60736021) |
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| 摘 要： | 针对处理实际工业过程中提取的建模样本不纯而导致故障检测失效的问题,提出一种新的融合Fisher判别分析-可能性C-均值聚类(FDA-PCMC)的核主元分析(KPCA)故障检测算法.通过FDA特征提取、初分类和PCMC聚类相结合的方代来实现建模样本的有效分类和提纯,然后使用KPCA进行实时故障检测.对Tennessee Eastman(TE)过程的仿真研宄结果表明了该算法的可行性和有效性.
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| 关 键 词： | 故障检测 Fisher判别分析-可能性C-均值聚类 核主元分析 |
| 收稿时间： | 2009/5/15 0:00:00 |
| 修稿时间： | 2009/9/4 0:00:00 |
A New KPCA Based Fault Detection Algorithm Integrating FDA-PCMC Based Sample Classification |
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| ZHU Zhi-bo,SONG Zhi-huan.A New KPCA Based Fault Detection Algorithm Integrating FDA-PCMC Based Sample Classification[J].Control and Decision,2010,25(4):542-545. |
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| Authors: | ZHU Zhi-bo SONG Zhi-huan |
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| Abstract: | In order to handle the invalidation problem of fault detection when the modeling samples got from the real industrial process is impure,a new kernel principal component analysis(KPCA) based fault detection algorithm integrating Fisher discriminant analysis-possibilistic C-means clustering(FDA-PCMC) is proposed.FDA based feature extraction, pre-classification and PCMC based clustering are proposed to classify and purify the modeling samples effectively,and KPCA is used for real-time fault detection.Simulatio... |
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| Keywords: | Fault detection Fisher discriminant analysis-possibilistic C-means clustering Kernel principal component analysis |
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