Weighted and constrained possibilistic C-means clustering for online fault detection and isolation

@article{Bahrampour2010WeightedAC,
  title={Weighted and constrained possibilistic C-means clustering for online fault detection and isolation},
  author={Soheil Bahrampour and Behzad Moshiri and Karim Salahshoor},
  journal={Applied Intelligence},
  year={2010},
  volume={35},
  pages={269-284}
}
In this paper, a new weighted and constrained possibilistic C-means clustering algorithm is proposed for process fault detection and diagnosis (FDI) in offline and online modes for both already known and novel faults. A possibilistic clustering based approach is utilized here to address some of the deficiencies of the fuzzy C-means (FCM) algorithm leading to more consistent results in the context of the FDI tasks by relaxing the probabilistic condition in FCM cost function. The proposed… CONTINUE READING

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