›› 2011, Vol. 24 ›› Issue (7): 137-.

• 论文 • 上一篇    下一篇

基于BP网络和D-S证据理论的齿轮箱故障诊断

顾秀江,姚竹亭,王煜杰,秦新红,刘永峰   

  1. (中北大学 机械工程与自动化学院,山西 太原 030051)
  • 出版日期:2011-07-15 发布日期:2011-08-16
  • 作者简介:顾秀江(1985—),男,硕士研究生。研究方向:智能传感与工业系统控制。

Fault Diagnosis of Gearbox Based on the BP Network and D-S Evidence Theory

 GU Xiu-Jiang, YAO Zhu-Ting, WANG Yu-Jie, QIN Xin-Hong, LIU Yong-Feng   

  1. (School of Mechanical Engineering & Automation,North University of China,Taiyuan 030051,China)
  • Online:2011-07-15 Published:2011-08-16

摘要:

为避免故障诊断中单一信息的固有缺陷,提高诊断精度,将改进的BP神经网络和D-S证据理论相结合,针对齿轮箱的3个测点,采用改进BP神经网络进行独立的局部故障诊断,以及采用D-S证据理论规则,将3个测点的神经网络输出结果进行融合,得到整个齿轮箱的故障诊断结果。通过分析可以看出,融合后的诊断结果更加精确,信任度更高。

关键词: BP网络, 故障诊断, D-S证据理论

Abstract:

In order to avoid inherent defect of single information in the fault diagnosis,and to improve the diagnostic accuracy,the improved BP neural network is combined with the D-S evidence theory.For the three gauge points of gear-box,the improved BP neural network is used for independent and local fault diagnosis,and then the neural network output results of them is fused by D-S evidence theory rules,and the whole gear-box fault diagnosis is obtained.Through the analysis,one can see that the fused diagnosis result is more accurate,and the trust is higher.

Key words: BP network;Fault diagnosis;D-S evidence theory

中图分类号: 

  • TP183