کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
10265716 | 458642 | 2005 | 7 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Data-based latent variable methods for process analysis, monitoring and control
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی شیمی
مهندسی شیمی (عمومی)
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چکیده انگلیسی
This paper gives an overview of methods for utilizing large process data matrices. These data matrices are almost always of less than full statistical rank, and therefore, latent variable methods are shown to be well suited to obtain useful subspace models from them for treating a variety of important industrial problems. An overview of the important concepts behind latent variable models is presented and the methods are illustrated with industrial examples in the following areas: (i) the analysis of historical databases and trouble-shooting process problems; (ii) process monitoring and FDI; (iii) extraction of information from novel multivariate sensors; (iv) process control in reduced dimensional subspaces. In each of these problems, latent variable models provide the framework on which solutions are based.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers & Chemical Engineering - Volume 29, Issue 6, 15 May 2005, Pages 1217-1223
Journal: Computers & Chemical Engineering - Volume 29, Issue 6, 15 May 2005, Pages 1217-1223
نویسندگان
John F. MacGregor, Honglu Yu, Salvador GarcÃa Muñoz, Jesus Flores-Cerrillo,