Multivariate statistical process monitors

Details Multivariate statistical process monitors Multivariate statistical process monitors

2006-06-13

2006-06-13

Thomson, W. (Department: 2123)

Data processing: structural design, modeling, simulation, and em

Modeling by mathematical expression

C702S179000, C702S181000, C702S196000, C702S198000, C700S030000, C700S049000

Reexamination Certificate

active

07062417

ABSTRACT:
An extended partial least squares (EPLS) approach for the condition monitoring of industrial processes is described. This EPLS approach provides two statistical monitoring charts to detect abnormal process behaviour as well as contribution charts to diagnose this behaviour. A theoretical analysis of the EPLS monitoring charts is provided, together with two application studies to show that the EPLS approach is either more sensitive or provides easier interpretation than conventional PLS.Generalised scores are calculated by constructing an augmented matrix, of the formin-line-formulae description="In-line Formulae" end="lead"?Z=[Y{dot over (:)}X],in-line-formulae description="In-line Formulae" end="tail"?where X is the predictor matrix and Y is the response matrix, and constructing a score matrix Tn=T*n−E*nin which T*nand E*nare generally of the form:Tn*=[Y⁢⁢⋮⁢⁢X]⁡[BPLS(n):]1⁢RnEn*=[En⁢⁢⋮⁢⁢Fn]⁡[BPLS(n):]1⁢Rnthe columns of the matrix T*nproviding the generalised t-scores and the columns of the matrix E*nthe generalised residual scores, where ℑ denotes an M×M identity matrix,BPLS(n)is the PLS regression matrix.

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