计算机与现代化 ›› 2010, Vol. 1 ›› Issue (5): 21-23.doi: 10.3969/j.issn.1006-2475.2010.05.007

• 人工智能 • 上一篇    下一篇

模糊RBF网络在电源车故障诊断中的应用

陆兵焱1,陈友龙2,张宗宜1   

  1. 1.海军航空工程学院青岛分院研究生队,山东 青岛 266041; 2.海军航空工程学院青岛分院四站教研室,山东 青岛 266041
  • 收稿日期:2009-11-25 修回日期:1900-01-01 出版日期:2010-05-10 发布日期:2010-05-10

Fault Diagnosis of Power Vehicle with RBF Fuzzy Neural Network

LU Bing-yan1, CHEN You-long2, ZHANG Zong-yi1   

  1. 1. Graduate Brigade, Qingdao Branch, Naval Aeronautical and Astronautical University, Qingdao 266041, China;2. Four-station Staff Room, Qingdao Branch, Naval Aeronautical and Astronautical University, Qingdao 266041, China
  • Received:2009-11-25 Revised:1900-01-01 Online:2010-05-10 Published:2010-05-10

摘要: 结合模糊理论与RBF神经网络构建了模糊RBF网络故障诊断法。在对某型电源车进行故障诊断的过程中,通过对RBF神经网络与模糊RBF网络故障诊断法进行比较,表明模糊RBF网络故障诊断法具有精度更高、收敛速度更快等特点。

关键词: 电源车, 模糊RBF网络, 故障诊断

Abstract: Combined with the fuzzy theory and the RBF neural network, this paper constructs the fault diagnostic method of fuzzy RBF network. In the process of the power vehicle fault diagnosis, through comparing the RBF neural network with the fuzzy RBF network, the result indicates that the fuzzy RBF network has the characteristics of higher precision and faster convergence speed etc.

Key words: power vehicle, fuzzy RBF network, fault diagnosis

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