Quality Monitoring Using Principal Component Analysis and Fuzzy Logic Application in Continuous Casting Process
Salah Bouhouche1, Malek Lahreche1, Abdelkrim Moussaoui2 & Jürgen Bast3 Show affiliations
- Iron and Steel Applied Research Unit – CSC, BP 196 Annaba, 23000, Algeria
- Electrical Engineering Laboratory (LGEG), University of Guelma, BP 401, 24000, Algeria
- HGUM, Institut für Maschinenbau, TU Bergakademie Freiberg, Cotta Stasse 4, D-9596, Algeria
American Journal of Applied Sciences, Volume 4, Issue 9, pp. 637–644 · doi.org/10.3844/ajassp.2007.637.644
Abstract
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.
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Bouhouche, S., Lahreche, M., Moussaoui, A. & Bast, J. (2007). Quality Monitoring Using Principal Component Analysis and Fuzzy Logic Application in Continuous Casting Process. American Journal of Applied Sciences, 4(9), 637–644. https://doi.org/10.3844/ajassp.2007.637.644
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