Weighted principal component analysis and its applications to improve FDC performance

@article{Yue2004WeightedPC,
  title={Weighted principal component analysis and its applications to improve FDC performance},
  author={H. H. Yue and Masayuki Tomoyasu},
  journal={2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601)},
  year={2004},
  volume={4},
  pages={4262-4267 Vol.4}
}
This paper discusses several practical issues encountered when applying principal component analysis (PCA) to fault detection and classification (FDC). Those issues presented a challenge to the success of PCA-model based process monitoring. Weighted PCA is proposed to address the issues. Two forms of weighted PCA are discussed: sample-wise and variable-wise. Sample-wise weighted PCA is used to address issues with model updating. By adapting models with process changes, the long-term validity of… CONTINUE READING
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