Title :
Development of a fault diagnosis system based on fuzzified neural networks in chemical processing plants
Author :
Kimura, Daisaku ; Nii, Manabu ; Yamaguchi, Takafumi ; Takahashi, Yutaka ; Yumoto, Takayuki
Author_Institution :
Grad. Sch. of Eng., Univ. of Hyogo, Himeji, Japan
Abstract :
Failure of chemical plants is very dangerous. Although such failure is solvable with extension of a sensor, and an increase of the operator, a huge amount of funds are required for these initiatives, and it cannot be realized easily. A model has been built by neural networks, and a diagnosis method using that model was proposed. In this paper, we propose the alternative diagnosis method using fuzzified neural networks.
Keywords :
chemical industry; fault diagnosis; fuzzy set theory; industrial plants; neural nets; chemical processing plants; diagnosis method; fault diagnosis system; fuzzified neural networks; Valves; Fault diagnosis; Fuzzified neural networks; Machine learning; Plant operation;
Conference_Titel :
World Automation Congress (WAC), 2010
Conference_Location :
Kobe
Print_ISBN :
978-1-4244-9673-0
Electronic_ISBN :
2154-4824