Author/Authors
Aras Norvilas، نويسنده , , Antoine Negiz، نويسنده , , Jeffrey DeCicco and Ali Cinar، نويسنده ,
DocumentNumber
1384357
Title Of Article
Intelligent process monitoring by interfacing knowledge-based systems and multivariate statistical monitoring
شماره ركورد
11620
Latin Abstract
An intelligent process monitoring and fault diagnosis environment has been developed by interfacing multivariate statistical
process monitoring (MSPM) techniques and knowledge-based systems (KBS) for monitoring multivariable process operation. The
real-time KBS developed in G2 is used with multivariate SPM methods based on canonical variate state space (CVSS) process
models. Fault detection is based on T2 charts of state variables. Contribution plots in G2 are used for determining the process
variables that have contributed to the out-of-control signal indicated by large T2 values, and G2 Diagnostic Assistant (GDA) is
used to diagnose the source causes of abnormal process behavior. The MSPM modules developed in Matlab are linked with G2.
This intelligent monitoring and diagnosis system can be used to monitor multivariable processes with autocorrelated, cross-
correlated, and collinear data. The structure of the integrated system is described and its performance is illustrated by simulation
studies.
From Page
341
NaturalLanguageKeyword
Knowledge-based system , Multivariate statistical process monitoring , Fault detection and diagnosis , canonical variate analysis , Statespace models
JournalTitle
Studia Iranica
To Page
350
To Page
350
Link To Document