Damage Identification in Structures Based on Integrated Wavelet Neural Networks

摘要：

The tight wavelet neural network was constituted taking the nonlinear Morlet wavelet radices as the stimulant function. The idiographic algorithm was presented. It can combine the advantages of wavelet analysis and neural networks. The integrated wavelet neural network damage identification system was set up based on both the information fusion technology and actual damage identification, which taking the sub-wavelet neural network as primary identification from different sides, then gained the conclusions through decision-making fusion. The realizable policy of the identification system and established principle of the sub-wavelet neural networks were given in the paper. It can be educed from the examples that it takes full advantage of diversified characteristic information, and improves the identification rate.

关键词： structure damage identification wavelet analysis integrated neural networks information fusion identification rate

作者: LUO Yuegang LIU Yubin ZHANG Songhe

作者单位: School of Civil Engineering and Architecture,Dalian Nationalities University,Dalian 116600,Liaoning,China

会议类型: 国际会议

会议名称: The 2008 International Symposium on Safety Science and Technology(2008年安全科学技术国际会议)

会议地点: 北京

会议语种:英文

页码: 1893-1897

在线出版日期: 2008-09-24（万方平台首次上网日期，不代表论文的发表时间）