A recursive multi-block PLS algorithm for monitoring industrial processes
被引:0
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作者:
Wang, X
论文数: 0引用数: 0
h-index: 0
机构:
Univ Manchester, Dept Mech Engn, Manchester M13 9PL, Lancs, EnglandUniv Manchester, Dept Mech Engn, Manchester M13 9PL, Lancs, England
Wang, X
[1
]
Kruger, U
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机构:
Univ Manchester, Dept Mech Engn, Manchester M13 9PL, Lancs, EnglandUniv Manchester, Dept Mech Engn, Manchester M13 9PL, Lancs, England
Kruger, U
[1
]
Leung, AYT
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机构:
Univ Manchester, Dept Mech Engn, Manchester M13 9PL, Lancs, EnglandUniv Manchester, Dept Mech Engn, Manchester M13 9PL, Lancs, England
Leung, AYT
[1
]
Lennox, B
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h-index: 0
机构:
Univ Manchester, Dept Mech Engn, Manchester M13 9PL, Lancs, EnglandUniv Manchester, Dept Mech Engn, Manchester M13 9PL, Lancs, England
Lennox, B
[1
]
机构:
[1] Univ Manchester, Dept Mech Engn, Manchester M13 9PL, Lancs, England
来源:
NEW TECHNOLOGIES FOR COMPUTER CONTROL 2001
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2002年
关键词:
multivariate quality control;
statistical process control;
large-scale systems;
model reduction;
process identification;
D O I:
暂无
中图分类号:
TP [自动化技术、计算机技术];
学科分类号:
0812 ;
摘要:
Industrial processes often present a large number of highly correlated variables that are frequently measured and consist of several operating units. For monitoring such processes multi-block partial least squares (MBPLS) has shown to be capable of dividing the variables according to operating units and can reduce the number variables that describe significant process variation with sufficient accuracy. As shown in this paper, MBPLS may run into difficulties when the process exhibits nonstationary behaviour. To overcome this deficiency, the development of recursive MBPLS is discussed including an application study that relates to a realistic simulation of a fluid catalytic cracking unit. Copyright (C) 2001 IFAC.