DocumentCode :
2750690
Title :
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
Link To Document :
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