Quality Monitoring Using Principal Component Analysis and Fuzzy Logic Application in Continuous Casting Process
This paper deals with non linear system monitoring, based on a combined use of Principal Components Analysis (PCA) and fuzzy logic to process and quality monitoring. PCA coupled to fuzzy logic was used to estimate the fault or defect according to the dynamic changes in the process inputs-outputs characterized by T2 Hoteling and Squared Prediction Error (SPE). Correlation between the relevant process variables and the importance of defects/faults was obtained by a reliable selection of a reduced set of relevant descriptors. The effectiveness of the computing procedure based on fuzzy rule proved by its application to quality estimation of the solidification process in continuous casting.
Copyright: © 2007 Salah Bouhouche, Malek Lahreche, Abdelkrim Moussaoui and Jürgen Bast. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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- Principal Component Analysis (PCA)
- Fuzzy Logic
- Fault Detection and Diagnosis (FDD)
- Quality Monitoring
- Continuous Casting Process