Fault Detection Based on Fuzzy Neural Networks – Application to Sugar Factory Evaporator
Jan Maciej Kościelny , Andrzej Ostasz , Piotr Wasiewicz
AbstractFuzzy and neural process modelling methods for purposes of fault detection have been discussed in the paper. Fuzzy neural networks and TSK models (Takagi-Sugeno-Kang’s models) have been used for modelling. Research results of modelling as well as fault detection algorithms have been presented. Research for the chosen evaporator of evaporation station at “Lublin” sugar factory has been performed. The features of methods mentioned above have been also discussed.
|Journal series||IFAC Proceedings Volumes, ISSN 1474-6670|
|Publication size in sheets||0.5|
|Conference||4th IFAC Symposium on Fault Detection, Supervision and Safety for Technical Processes 2000 (SAFEPROCESS 2000), 14-06-2000 - 16-06-2000, Budapest, Węgry|
|Keywords in English||artificial intelligence, fuzzy modelling, neural-network models, fault detection, computer applications|
|Citation count*||8 (2015-05-30)|
* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.