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Research on Gear-box Fault Diagnosis Method Based on Adjusting-learning-rate PSO Neural Network
被引:3
作者:
潘宏侠
马清峰
机构:
[1] College of Mechanical Engineering & Automatization North University of China
[2] Taiyuan 030051
关键词:
particle swarm optimization;
neural network;
fault diagnosis method;
compound-box;
D O I:
10.19884/j.1672-5220.2006.06.007
中图分类号:
TP183 [人工神经网络与计算];
学科分类号:
081104 ;
0812 ;
0835 ;
1405 ;
摘要:
Based on the research of Particle Swarm Optimization (PSO) learning rate, two learning rates are changed linearly with velocity-formula evolving in order to adjust the proportion of social part and cognitional part; then the methods are applied to BP neural network training, the convergence rate is heavily accelerated and locally optional solution is avoided. According to actual data of two levels compound-box in vibration lab, signals are analyzed and their characteristic values are abstracted. By applying the trained BP neural networks to compound-box fault diagnosis, it is indicated that the methods are sound effective.
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页码:29 / 32
页数:4
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