Title :
Condition Monitoring and Faults Recognizing of Dish Centrifugal Separator by Artifical Neural Network Combined with Expert System
Author :
Xiaojian, Ma ; Xuehui, Gan
Author_Institution :
Eng. Res. Center of Adv. Textile Machinery, Donghua Univ., Shanghai, China
Abstract :
Structure of dish centrifugal separator is described firstly. According to the characters of the dish centrifugal separator´s main faults, a serial of methods of extracting fault feature are figured out. In the process of classifying and recognizing faults, the advantages of expert system and artificial neural network are combined together. The experiment results show that the methods presented here are effective.
Keywords :
chemical technology; condition monitoring; diagnostic expert systems; fault diagnosis; feature extraction; neural nets; pattern classification; production engineering computing; separation; signal classification; artificial neural network; condition monitoring; dish centrifugal separator; expert system; fault classification; fault feature extraction; fault recognition; Artificial neural networks; Condition monitoring; Expert systems; Fault diagnosis; Feature extraction; Gears; Neural networks; Particle separators; Signal processing; Signal sampling; Fault recognizing; Walsh transformation; artificial neural network; condition monitoring; dish centrifugal separator; expert system; helical gear; wavelet packet analysis;
Conference_Titel :
Natural Computation, 2009. ICNC '09. Fifth International Conference on
Conference_Location :
Tianjin
Print_ISBN :
978-0-7695-3736-8
DOI :
10.1109/ICNC.2009.511
