DocumentCode
2190938
Title
Machinery Fault Diagnosis System Based on Fuzzy Neural Networks
Author
Bai Xingli ; Men Hongyun
Author_Institution
Dept. of Comput. Sci. & Eng., Henan Inst. of Eng., Zhengzhou, China
fYear
2009
fDate
20-22 Sept. 2009
Firstpage
1
Lastpage
4
Abstract
A fuzzy neural network fault diagnosis fault model, which is set up by fusing fuzzy Classification and traditional neural network, is applied to fault diagnosis of mine fan. In order to verify the effectiveness and feasibility of the algorithm, the simulation model based on fuzzy neural network has been set up in the MATLAB environment. Simulation results show that the performance of fuzzy neural network is superior to traditional BP network.
Keywords
fans; fault diagnosis; fuzzy neural nets; mathematics computing; mechanical engineering computing; mining; pattern classification; BP network; MATLAB environment; fuzzy classification; fuzzy neural network; machinery fault diagnosis system; mine fan; Computational modeling; Computer science; Fault diagnosis; Fuzzy logic; Fuzzy neural networks; Fuzzy sets; Fuzzy systems; Machinery; Mathematical model; Neural networks;
fLanguage
English
Publisher
ieee
Conference_Titel
Management and Service Science, 2009. MASS '09. International Conference on
Conference_Location
Wuhan
Print_ISBN
978-1-4244-4638-4
Electronic_ISBN
978-1-4244-4639-1
Type
conf
DOI
10.1109/ICMSS.2009.5305391
Filename
5305391
Link To Document