[1]朱大奇,于盛林.电子电路故障诊断的神经网络数据融合算法[J].东南大学学报(自然科学版),2001,31(6):87-90.[doi:10.3969/j.issn.1001-0505.2001.06.021] 　Zhu Daqi,Yu Shenglin.Neural Network Data Fusion Algorithm of Circuit Fault Diagnosis[J].Journal of Southeast University (Natural Science Edition),2001,31(6):87-90.[doi:10.3969/j.issn.1001-0505.2001.06.021] 点击复制 电子电路故障诊断的神经网络数据融合算法() 分享到： var jiathis_config = { data_track_clickback: true };

31

2001年第6期

87-90

2001-11-20

文章信息/Info

Title:
Neural Network Data Fusion Algorithm of Circuit Fault Diagnosis

1 南京航空航天大学测试工程系, 南京 210016; 2 安徽工业大学工业自动化系, 马鞍山 243002
Author(s):
1 Department of Testing and Measurement Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China; 2 Industrial Automation Department, Anhui University of Science And Technology, Ma’anshan 243002, China)

Keywords:

TP277;TH137.3
DOI:
10.3969/j.issn.1001-0505.2001.06.021

Abstract:
In order to solve uncertain problem of circuit fault diagnosis, a fuzzy neural network fault classifier is designed based on BP neural network and fuzzy logical theory, and it is used in fault diagnosis. By measuring the temperature and voltage of circuit components, the membership function of two sensors to circuit component is obtained and the data fusion is made by using fuzzy BP neural network classifier. Thus the fusion fault membership function of all circuit components and the fault component can be found. By comparing the diagnosis results based on separate original data and fused date, it is shown that the latter is more accurate than the former in circuit fault recognition.

参考文献/References:

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