DocumentCode
533584
Title
Fault diagnosis of air-conditioning fan based on RBF neural networks algorithm
Author
Yi, Wang
Author_Institution
Dept. of Building Environ. & Equip. Eng., Donghua Univ., Shanghai, China
Volume
1
fYear
2010
fDate
1-2 Aug. 2010
Firstpage
304
Lastpage
306
Abstract
In order to overcome the problems of slow rate of convergence, falling easily into local minimum and instability of learning performance caused by initial value in BP algorithm, the diagnosis method based on RBF neural networks was proposed. And the diagnosis method is applied to air-conditioning fan fault diagnosis. The result shows that RBF network has very high learning convergence speed and better classifying performance. RBF network has good practicality in the field of equipment fault diagnosis.
Keywords
air conditioning; backpropagation; fans; fault diagnosis; learning (artificial intelligence); mechanical engineering computing; quality assurance; radial basis function networks; RBF neural networks algorithm; air conditioning fan fault diagnosis; backpropagation algorithm; diagnosis method; equipment fault diagnosis; high learning convergence speed; Classification algorithms; Convergence; Cryptography; Air-conditioning fan; Fault Diagnosis; RBF neural networks;
fLanguage
English
Publisher
ieee
Conference_Titel
Circuits,Communications and System (PACCS), 2010 Second Pacific-Asia Conference on
Conference_Location
Beijing
Print_ISBN
978-1-4244-7969-6
Type
conf
DOI
10.1109/PACCS.2010.5626978
Filename
5626978
Link To Document