Process Fault Diagnosis using Recursive Multivariate Statistical Process Control
| Authors: | Wang Xun, Queen's University Belfast, United Kingdom
Krüger Uwe, Queen's University Belfast, United Kingdom
Irwin George W., Queen's University Belfast, United Kingdom |
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| Topic: | 6.4 Safeprocess |
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| Session: | Applications of Fault Diagnosis and Fault Tolerant Control |
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| Keywords: | Recursive Algorithms, Statistical Process Control, Process Models, Data Reduction, Fault Diagnosis |
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Abstract
Over the last few years, recursive extensions to multivariate statistical process control (MSPC) techniques have gained attention for their ability in monitoring large-scale, time-varying processes. Although recursive MSPC techniques have been successfully applied in detecting faulty conditions, little interest has been shown in utilising them for diagnosis purposes. This paper addresses this issue and introduces new fault diagnosis charts that rely on recursive MSPC models. The utility of these is demonstrated using an application study on a simulation of a complex chemical process.
