DocumentCode :
551204
Title :
FICA-PNN fault diagnosis for penicillin fermentation process
Author :
Yang Qing ; Yao Jingtang ; Zhang Xu ; Chao Xiaojie
Author_Institution :
Sch. of Inf. Sci. & Eng., Shenyang Ligong Univ., Shenyang, China
fYear :
2011
fDate :
22-24 July 2011
Firstpage :
4351
Lastpage :
4354
Abstract :
A novel ensemble approach based on fast independent component analysis and probabilistic neural network (FICA-PNN) is presented to diagnose faults in the fed-batch penicillin fermentation process. FICA is used to extract fastly the information of a non-Gaussian process. PNN is used as a classifier for diagnosing faults. The experimental results clearly demonstrate that the proposed approach is faster and more efficient and has higher accuracy rate compared to conventional fault diagnosis approaches.
Keywords :
Gaussian processes; fault diagnosis; fermentation; independent component analysis; neural nets; pharmaceutical technology; FICA-PNN; fast independent component analysis; fault diagnosis; nonGaussian process; penicillin fermentation process; probabilistic neural network; Algorithm design and analysis; Classification algorithms; Fault diagnosis; Independent component analysis; Monitoring; Probabilistic logic; Substrates; Fast Independent Component Analysis; Fault Diagnosis; Fica-Pnn; Penicillin Fermentation Process; Probabilistic Neural Network;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control Conference (CCC), 2011 30th Chinese
Conference_Location :
Yantai
ISSN :
1934-1768
Print_ISBN :
978-1-4577-0677-6
Electronic_ISBN :
1934-1768
Type :
conf
Filename :
6001549
Link To Document :
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