Research on Fault Diagnosis of Gearbox Based on Particle Swarm Optimization Algorithm

Author

Hongxia, Pan ; Qingfeng, Ma ; Xiuye, Wei

Author_Institution

Sch. of Mech. Eng. & Autoimmunization, North Univ. of China, Taiyuan

fYear

2006

fDate

3-5 July 2006

Firstpage

32

Lastpage

37

Abstract

In this paper, base on studying learning rate of PSO, in order to adjust the social part and the cognition part proportions, learning rate change linearly with velocity-formula evolving is made; the BP neural network PSO training heavily increases the congruence speed of the networks to avoid involving local extremum. According to actual data of two levels gearbox in vibration lab, signals are analyzed and their feature values are abstracted. By applying trained BP neural networks to diagnosing gearbox faults got sound effect

Keywords

fault diagnosis; gears; learning (artificial intelligence); mechanical engineering computing; neural nets; particle swarm optimisation; BP neural network; cognition part proportions; fault diagnosis; gearbox; learning rate change; particle swarm optimization; velocity-formula; Algorithm design and analysis; Cognition; Fault diagnosis; Laboratories; Mechanical engineering; Mechatronics; Neural networks; Particle swarm optimization; Signal analysis; Vibrations; Fault diagnosis; Gearbox; Neural network; Particle swarm optimization;

fLanguage

English

Publisher

ieee

Conference_Titel

Mechatronics, 2006 IEEE International Conference on

Conference_Location

Budapest

Print_ISBN

0-7803-9712-6

Electronic_ISBN

0-7803-9713-4

Type

conf

DOI

10.1109/ICMECH.2006.252492

Filename

4018327