Survey on the theoretical research and engineering applications of multivariate statistics process monitoring algorithms: 2008-2017

被引:180
作者
Wang, Youqing [1 ,2 ]
Si, Yabin [2 ]
Huang, Biao [3 ]
Lou, Zhijiang [2 ]
机构
[1] Shandong Univ Sci & Technol, Coll Elect Engn & Automat, Qingdao, Peoples R China
[2] Beijing Univ Chem Technol, Coll Informat Sci & Technol, Beijing, Peoples R China
[3] Univ Alberta, Dept Chem & Mat Engn, Edmonton, AB, Canada
基金
中国国家自然科学基金;
关键词
multivariate statistical process monitoring; principal component analysis; partial least squares; INDEPENDENT COMPONENT ANALYSIS; NONNEGATIVE MATRIX FACTORIZATION; NEAR-INFRARED SPECTROSCOPY; LEAST-SQUARES REGRESSION; VECTOR DATA DESCRIPTION; NON-GAUSSIAN PROCESSES; FAULT-DETECTION; BATCH PROCESSES; MULTIMODE PROCESS; NONLINEAR PROCESSES;
D O I
10.1002/cjce.23249
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
Multivariate statistical process monitoring (MSPM) methods are significant for improving production efficiency and enhancing safety. However, to the authors' best knowledge, there is no survey paper providing statistics of published papers over the past decade. In this paper, several issues related to MSPM methods are reviewed and studied. First, the annual publication numbers of journal articles concerning MSPM are provided to show the active development of this important research field and to point out several promising directions in the future. Second, the annual numbers of patents are also shown to demonstrate the practicality of different MSPM methods. Particularly, this paper also lists and analyzes the number of MSPM-related publications in China. The statistics indicate that Chinese researchers and engineers may have different viewpoints from those of other countries, which results in different development trends of MSPM in China.
引用
收藏
页码:2073 / 2085
页数:13
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