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

Volume

2

fYear

2009

fDate

14-16 Aug. 2009

Firstpage

203

Lastpage

207

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Natural Computation, 2009. ICNC '09. Fifth International Conference on

Conference_Location

Tianjin

Print_ISBN

978-0-7695-3736-8

Type

conf

DOI

10.1109/ICNC.2009.511

Filename

5365858