首页> 外文期刊>东华大学学报(英文版) >Research on Gear-box Fault Diagnosis Method Based on Adjusting-learning-rate PSO Neural Network
【24h】

Research on Gear-box Fault Diagnosis Method Based on Adjusting-learning-rate PSO Neural Network

机译:基于学习率PSO神经网络的齿轮箱故障诊断方法研究

获取原文
获取原文并翻译 | 示例
       

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.
机译:基于粒子群优化(PSO)学习率的研究,两种学习率随速度公式而发生线性改变,以调整社会部件和认知部分的比例;然后将该方法应用于BP神经网络训练,收敛速度大量加速,避免了局部可选的解决方案。根据振动实验室中的两个级别复合盒的实际数据,分析了信号,并抽出其特征值。通过将训练的BP神经网络应用于复合盒故障诊断,表示这些方法是声音有效的。

著录项

获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号