Wavelet Neural Network Based on Modified PSO and Its Application in Fault Diagnosis of Gearbox

Author

Ying, Liu ; Jie, Liu ; Hongwei, Mao ; Hongxia, Pan

Author_Institution

Tianjin Key Lab. of High Speed Cutting & Precision Machining, Tianjin Univ. of Technol. & Educ., Tianjin, China

Volume

3

fYear

2009

fDate

14-16 Aug. 2009

Firstpage

338

Lastpage

342

Abstract

A modified particle swarm optimization--compound model PSO with stochastic inertia weigh is put forward and used to optimize the parameters of wavelet neural network. The trained wavelet neural-network is applied to the fault diagnosis experiment of gearbox. The experimental result indicates that the wavelet neural-network training method based on the modified PSO is effective. This is an available approach to solve the problems on condition monitoring and fault diagnosis.

Keywords

condition monitoring; fault diagnosis; gears; learning (artificial intelligence); mechanical engineering computing; neural nets; particle swarm optimisation; stochastic processes; wavelet transforms; condition monitoring; gearbox fault diagnosis; modified PSO; modified particle swarm optimization; stochastic inertia weigh; wavelet neural-network training method; Computer networks; Condition monitoring; Educational technology; Fault diagnosis; Laboratories; Machining; Neural networks; Particle swarm optimization; Stochastic processes; Wavelet 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.2009.485

Filename

5363243