Study on fault diagnosis of elevator based on neural network information fusion technology

doi:10.3778/j.issn.1002-8331.2010.14.069

Computer Engineering and Applications ›› 2010, Vol. 46 ›› Issue (14): 231-234.DOI: 10.3778/j.issn.1002-8331.2010.14.069

• 工程与应用 • Previous Articles Next Articles

Study on fault diagnosis of elevator based on neural network information fusion technology

LI Duan，AI Yong-le

School of Electrical Engineering and Automation，Henan Polytechnic University，Jiaozuo，Henan 454000，China

Received:2008-11-11 Revised:2009-01-20 Online:2010-05-11 Published:2010-05-11
Contact: LI Duan

神经网络信息融合用于电梯故障诊断的研究

李端，艾永乐

河南理工大学电气工程与自动化学院，河南焦作 454000

通讯作者: 李端

Abstract

Abstract: Researchers have studied on elevator fault diagnosis，but timeliness is limited，and can’t discover reason of the faults accurately.To solve these problems，this paper introduces the multi-information fusion technology to the fault diagnosis of elevator control system.The fault diagnosis model：A combination of fuzzy neural network and D-S evidential theory is set up.The BP neural network’s algorithm has been revised in order to enhances its study speed and the ability for precise diagnosis from the D-S evidential theory is fully made use of.The simulation of the fault phenomena has the good effect of this fault diagnosis system.

Key words: fault diagnosis, information fusion, fuzzy neural network, D-S evidential theory

摘要： 针对传统电梯故障诊断系统实时性有限、故障定位准确率低等问题，将多信息融合技术引入到电梯故障诊断中来，建立了基于模糊神经网络和D-S证据理论相结合的故障诊断模型。为了提高神经网络的训练速度和推广能力，采用了正则化算法对BP网络算法进行修改，并且利用D-S证据理论对神经网络的诊断结果进行决策融合，仿真结果表明了此方法有效地提高了故障诊断的准确率。

关键词: 故障诊断, 信息融合, 模糊神经网络, D-S证据理论

CLC Number:

TU857

LI Duan，AI Yong-le
. Study on fault diagnosis of elevator based on neural network information fusion technology[J]. Computer Engineering and Applications, 2010, 46(14): 231-234.

李端，艾永乐. 神经网络信息融合用于电梯故障诊断的研究[J]. 计算机工程与应用, 2010, 46(14): 231-234.

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Study on fault diagnosis of elevator based on neural network information fusion technology

神经网络信息融合用于电梯故障诊断的研究

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