Neural Network Method for Real-time Earthquake Induced Damage Assessment

摘要：

It is expected that damages of transportation link including highway bridges cause serious interference of traffic function and recovery efforts, when a large earthquake occurs to a densely populated urban area. This research proposes the method of assessing the damages of bridge pier to provide real time earthquake damage information for disaster mitigation. Dynamic experimental data were used to verify the proposed method. Amplitude ratio and phase difference which corresponded well to the damages were selected a damage index. The proposed method is able to provide the useful information for damages more quickly than frequency domain analysis method.

关键词： Highway bridge pier Earthquake disaster prevention Real--time Damage evaluation Neural networks Structural identification

作者: Yokoyama Koichi Kuroda Satoshi Rafiquzzaman A. K. M. Harada Takao

作者单位: Professor, Dr. Eng., Dept. of Urban and Civil Eng., Ibaraki University, Japan Structural Engineer, MS, Japan Transportation Consultants, Inc., Japan Researcher, Dr. Eng., Venture Business Laboratory, Ibaraki Univ., Japan Lecturer, Dept. of Urban and Civil Eng., Ibaraki University, Japan

会议类型: 国际会议

会议名称: 结构、材料与环境健康监测国际会议(International Conference on Health Monitoring og Structure,Material and Environment)

会议地点: 南京

会议语种:英文

页码: 397-401

在线出版日期: 2007-10-16（万方平台首次上网日期，不代表论文的发表时间）