Title :
Research on fault diagnosis method based on Modified Elman Neural Network
Author :
Li, Jiejia ; Zhou, Hao ; Guo, Tongying
Author_Institution :
School of Information and Control Engineering, Shenyang Jianzhu University, Liaoning, 110168, China
Abstract :
This paper presents fault diagnosis method in aluminum electrolysis based on Modified Elman Neural Network. According to the mechanism of fault occurring in aluminum electrolysis, time and type of fault is determined by neural network. Simulation results show that the fault diagnosis method based on Modified Elman Neural Network can predict fault during aluminum electrolysis rapidly and accurately. And it has a certain value in engineering applications.
Keywords :
Aluminum; Anodes; Artificial neural networks; Data models; Electrochemical processes; Fault diagnosis; Resistance; Modified Elman Neural Network; aluminum electrolysis; fault diagnosis;
Conference_Titel :
Information Science and Engineering (ICISE), 2010 2nd International Conference on
Conference_Location :
Hangzhou, China
Print_ISBN :
978-1-4244-7616-9
DOI :
10.1109/ICISE.2010.5691755
