%0 Journal Article
%T Fault diagnosis of elevator control system based on information fusion<br>基于信息融合技术的电梯控制系统故障诊断*
%A BAO Jian
%A LIU Xiao-lei
%A <br>包健
%A 刘晓蕾
%J 计算机应用研究
%D 2011
%I 
%X An method which based on information fusion fault diagnosis is proposed for the elevator control system because of its difficult and low diagnosis rate, while optimizing the network learning rate and slopes of activation functions that improve on the Back-propagation (BP) neural network and then make the network have more capable of nonlinear classification and higher convergent efficiency. Meanwhile, elevator control signals and running parameters are regard as the characteristics of neural network classifier, and then apply the Dempster-Shafer (D-S) evidence theory fusing the result of multiple classifiers. Through making the basic reliability distribution of the evidence theory not completely depending on the expert subjective valuations, the impersonal valuation is realized. The method has high stability and accuracy. Finally, experimental results show the effectiveness of the algorithm.
%K BP neural network
%K D-S evidence theory
%K information fusion
%K fault diagnosis<br>BP神经网络
%K D-S证据理论
%K 信息融合
%K 故障诊断
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=ADCD3C54C7C4E18FA09D70F99B6EF33E&yid=9377ED8094509821&vid=D3E34374A0D77D7F&iid=38B194292C032A66&sid=F26986CDF689DBC4&eid=11632AEF1E1F2092&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=14