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
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;
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
DOI :
10.1109/ICMSS.2009.5305391
