Research Article Open Access

Quality Monitoring Using Principal Component Analysis and Fuzzy Logic Application in Continuous Casting Process

Salah Bouhouche1, Malek Lahreche1, Abdelkrim Moussaoui2 and Jürgen Bast3
  • 1 Iron and Steel Applied Research Unit – CSC, BP 196 Annaba, 23000, Algeria
  • 2 Electrical Engineering Laboratory (LGEG), University of Guelma, BP 401, 24000, Algeria
  • 3 HGUM, Institut für Maschinenbau, TU Bergakademie Freiberg, Cotta Stasse 4, D-9596, Algeria

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.

American Journal of Applied Sciences
Volume 4 No. 9, 2007, 637-644

DOI: https://doi.org/10.3844/ajassp.2007.637.644

Submitted On: 1 April 2007 Published On: 30 September 2007

How to Cite: 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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Keywords

  • Principal Component Analysis (PCA)
  • Fuzzy Logic
  • Fault Detection and Diagnosis (FDD)
  • Quality Monitoring
  • Continuous Casting Process