计算机工程与应用2012，Vol.48Issue(14)：231-234,4.DOI:10.3778/j.issn.1002-8331.2012.14.048
构造型神经网络在故障诊断中的应用研究
Application research of constructive neural networks on fault diagnosis
摘要
Abstract
A new fault diagnosis algorithm can be used to resolve the problem of fault diagnosis with prior knowledge more effectively. Taking the prior sample point as the center, using inner product to judge sample data similarity, it carries on the cluster analysis. It makes a super-plane intersect a sphere in the characteristics of the space, obtains a spherical covering area, thus transforms the neural network training question as the set of points cover question. Based on constructive neural networks, the algorithm's characteristic is that the sample data of fault can be handled directly. Because the cover center is determined, it constructs out the least element hidden layer network structure. This new algorithm can reduce the long training time and learning complexity of traditional neural networks. Computer simulation results confirm the effectiveness of the algorithm.关键词
构造型神经网络/故障诊断/覆盖/算法Key words
constructive neural networks/ fault diagnosis/ covering/ algorithm分类
信息技术与安全科学引用本文复制引用
喻晓莉,黎泽伦,倪彦..构造型神经网络在故障诊断中的应用研究[J].计算机工程与应用,2012,48(14):231-234,4.基金项目
重庆市教委基金(No.101412). （No.101412）
