Title :
Improved WNN to Rotating Machinery Fault Diagnosis
Author :
Xu, Jinli ; Huang, Yuan ; Duan, Ying
Author_Institution :
Sch. of Mech. & Electron. Eng., Wu Han Univ. of Technol., WuHan, China
Abstract :
The improved algorithm of WNN based on BP was proposed in this paper. Theoretical analysis and simulation result show it avoids both the blindness of framework designs for BP neural networks and the problem of nonlinear optimizations, such as local optimization. So it can simplify the training of neural networks. It has better abilities in function learning and generalization. This algorithm was successfully applied to rotating machinery fault diagnosis. Therefore it has wide application prospect.
Keywords :
backpropagation; fault diagnosis; neural nets; optimisation; production engineering computing; production equipment; BP neural networks; WNN algorithm; backpropagation neural network; function learning; neural network training; nonlinear optimization problem; rotating machinery fault diagnosis; wavelet neural network; Analytical models; Computational modeling; Computer science; Design optimization; Fault diagnosis; Machinery; Neural networks; Neurons; Time frequency analysis; Wavelet analysis;
Conference_Titel :
Computational Intelligence and Software Engineering, 2009. CiSE 2009. International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-4507-3
Electronic_ISBN :
978-1-4244-4507-3
DOI :
10.1109/CISE.2009.5364431
