International Journal of
Physical Sciences

  • Abbreviation: Int. J. Phys. Sci.
  • Language: English
  • ISSN: 1992-1950
  • DOI: 10.5897/IJPS
  • Start Year: 2006
  • Published Articles: 2533

Full Length Research Paper

New monitoring method based principal component analysis and fuzzy clustering

Khaled Ouni1*, Hedi Dhouibi1, Lotfi Nabli2 and Hassani Messaoud2
1The High Institute of Applied Sciences and Technology of Kairouan, Kairouan, Avenue Beit ElHekma, 3100 Kairouan, Tunisia. 2The National Engineering School of Monastir, Avenue Ibn ElJazzar, 5019 Monastir, Tunisia.
Email: [email protected]

  •  Accepted: 07 May 2012
  •  Published: 16 May 2013


This work concerns the principal component analysis applied to the supervision of quality parameters of the flour production line. Our contribution lies in the combined use of the principal component analysis technique and the clustering algorithms in the field of production system diagnosis. This approach allows detecting and locating the system defects, based on the drifts of the product quality parameters. A comparative study between the classification performance by clustering algorithms and the principal component analysis has been proposed. Locating parameters in defect is based on the technique of fault direction in partial least square.


Key words: Fuzzy clustering, fault detection, fault location, principal component analysis (PCA).