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PCA as tool for intelligent ultrafiltration for reverse osmosis seawater desalination pretreatment

(2017) DESALINATION. 419. p.188-196
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Abstract
A novel fouling monitoring methodology based on principal component analysis (PCA) has been validated using transmembrane pressure (TMP) data of a pilot-scale pressurized ultrafiltration (UF) system operated with seawater. The evolution of membrane fouling was investigated to determine its relation to the used cleaning strategy on the one hand and the quality of the raw seawater on the other hand. The developed models showed that in terms of cleaning efficiency there are no significant differences between the standard and optimized backwashing protocols that were employed. This confirms the hypothesis of being able to use the optimized operation in a sustainable manner and benefit from lower cleaning frequencies. In addition, it has been demonstrated that the use of PCA as a monitoring technique to detect abnormal fouling behaviour is a robust tool. By using PCA, decisions on cleaning sequences or frequencies could be taken dynamically instead of running the system with fixed cycles.
Keywords
Principal component analysis, Desalination, Fouling, Ultrafiltration, Seawater, MEMBRANE

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Citation

Please use this url to cite or link to this publication:

Chicago
Naessens, Wouter, Thomas Maere, G Gilabert-Oriol, V Garcia-Molina, and Ingmar Nopens. 2017. “PCA as Tool for Intelligent Ultrafiltration for Reverse Osmosis Seawater Desalination Pretreatment.” Desalination 419: 188–196.
APA
Naessens, W., Maere, T., Gilabert-Oriol, G., Garcia-Molina, V., & Nopens, I. (2017). PCA as tool for intelligent ultrafiltration for reverse osmosis seawater desalination pretreatment. DESALINATION, 419, 188–196.
Vancouver
1.
Naessens W, Maere T, Gilabert-Oriol G, Garcia-Molina V, Nopens I. PCA as tool for intelligent ultrafiltration for reverse osmosis seawater desalination pretreatment. DESALINATION. 2017;419:188–96.
MLA
Naessens, Wouter, Thomas Maere, G Gilabert-Oriol, et al. “PCA as Tool for Intelligent Ultrafiltration for Reverse Osmosis Seawater Desalination Pretreatment.” DESALINATION 419 (2017): 188–196. Print.
@article{8542299,
  abstract     = {A novel fouling monitoring methodology based on principal component analysis (PCA) has been validated using transmembrane pressure (TMP) data of a pilot-scale pressurized ultrafiltration (UF) system operated with seawater. The evolution of membrane fouling was investigated to determine its relation to the used cleaning strategy on the one hand and the quality of the raw seawater on the other hand. The developed models showed that in terms of cleaning efficiency there are no significant differences between the standard and optimized backwashing protocols that were employed. This confirms the hypothesis of being able to use the optimized operation in a sustainable manner and benefit from lower cleaning frequencies. In addition, it has been demonstrated that the use of PCA as a monitoring technique to detect abnormal fouling behaviour is a robust tool. By using PCA, decisions on cleaning sequences or frequencies could be taken dynamically instead of running the system with fixed cycles.},
  author       = {Naessens, Wouter and Maere, Thomas and Gilabert-Oriol, G and Garcia-Molina, V and Nopens, Ingmar},
  issn         = {0011-9164},
  journal      = {DESALINATION},
  keyword      = {Principal component analysis,Desalination,Fouling,Ultrafiltration,Seawater,MEMBRANE},
  language     = {eng},
  pages        = {188--196},
  title        = {PCA as tool for intelligent ultrafiltration for reverse osmosis seawater desalination pretreatment},
  url          = {http://dx.doi.org/10.1016/j.desal.2017.06.018},
  volume       = {419},
  year         = {2017},
}

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