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基于多元统计分析的过程监测研究 学位论文
硕士, 沈阳: 中国科学院沈阳自动化研究所, 2017
Authors:  王中伟
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主元分析方法  支持向量数据描述  谱聚类  多模态过程监测  局部-全局模型  
Fault detection based on global-local PCA-SVDD for multimode processes 会议论文
Proceedings of 2017 9th International Conference On Modelling, Identification and Control, ICMIC 2017, Kunming, China, July 10-12, 2017
Authors:  Li S(李帅);  Zhou XF(周晓锋);  Shi HB(史海波);  Wang ZW(王中伟)
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fault detection  monitoring  multimode industrial processes  mode division  global-local PCA-SVDD  
Multimode processes monitoring using global–local MIC-PCA-SVDD 会议论文
Lecture Notes in Electrical Engineering, Kunming, China, July 10-12, 2017
Authors:  Li S(李帅);  Zhou XF(周晓锋);  Shi HB(史海波);  Wang ZW(王中伟)
View  |  Adobe PDF(370Kb)  |  Favorite  |  View/Download:54/14  |  Submit date:2018/06/19
Monitoring  Multimode processes  Multimode division  Global–local MIC-PCA-SVDD  
Monitoring based on MIC-PCA and SVDD for industrial process 会议论文
Proceedings of 2017 IEEE 2nd Advanced Information Technology, Electronic and Automation Control Conference, IAEAC 2017, Chongqing, China, March 25-26, 2017
Authors:  Wang ZW(王中伟);  Li S(李帅);  Song H(宋宏);  Zhou XF(周晓锋)
View  |  Adobe PDF(891Kb)  |  Favorite  |  View/Download:153/24  |  Submit date:2017/12/11
Principal Component Analysis  Support Vector Data Description  Maximal Information Coefficient  Process Monitoring  Industrial Process  
Correlated and weakly correlated fault detection based on variable division and ICA 期刊论文
Computers and Industrial Engineering, 2017, 卷号: 112, 页码: 320-335
Authors:  Li S(李帅);  Zhou XF(周晓锋);  Pan FC(潘福成);  Shi HB(史海波);  Li KT(李开拓);  Wang ZW(王中伟)
View  |  Adobe PDF(1716Kb)  |  Favorite  |  View/Download:191/31  |  Submit date:2017/09/18
Fault Detection  Monitoring  Variable Division  Correlated And Weakly Correlated Variables  Independent Component Analysis  
基于对数变换和最大信息系数PCA的过程监测 期刊论文
科学技术与工程, 2017, 卷号: 17, 期号: 16, 页码: 259-265
Authors:  王中伟;  宋宏;  李帅;  周晓锋
View  |  Adobe PDF(549Kb)  |  Favorite  |  View/Download:150/21  |  Submit date:2017/07/17
主元分析方法  最大信息系数  对数变换  过程监测