| Experiment Verification of Damage Detection for Offshore Platforms by Neural Networks |
| |
| 作者姓名： | 刁延松 李华军 石湘 王树青 |
| |
| 作者单位： | Engineering College Ocean University of China Qingdao 266071 China，Civil Engineering College Qingdao Technological University Qingdao 266033 China，Engineering College Ocean University of China Qingdao 266071 China，Engineering College Ocean University of China Qingdao 266071 China，Engineering College Ocean University of China Qingdao 266071 China |
| |
| 基金项目： | 国家自然科学基金;山东省青岛市自然科学基金 |
| |
| 摘 要： | 1 .Introduction Large civil engineering structures are exposed to various external loads such as earthquakes ,winds ,traffic and wave loads during their lifetime . The structures may become deteriorated and de-graded withtime in an unexpected way, which m…
|
| 关 键 词： | 损伤探测 神经网络 近海平台 钢结构 |
| 收稿时间： | 2005-11-08 |
Experiment Verification of Damage Detection for Offshore Platforms by Neural Networks |
| |
| DIAO Yan-song,LI Hua-jun,SHI Xiang,WANG Shu-qing.Experiment Verification of Damage Detection for Offshore Platforms by Neural Networks[J].China Ocean Engineering,2006,20(3):351-360. |
| |
| Authors: | DIAO Yan-song LI Hua-jun SHI Xiang WANG Shu-qing |
| |
| Abstract: | In the present work, damage detection for offshore platforms is divided into three steps. Firstly, the located direction of the damaged member is determined by the probabilistic neural network with input of the change rate of normalized modal frequency. Secondly, the profile and layer of the damaged member is also determined by the probabilistic neural network with input of the normalized damage-signal index. Finally, the damage extent is determined by the back propagation neural networks with input of the squared change rate of modal frequency. So the size of the network and the training time can be reduced greatly. All these networks are trained with simulated data obtained from the finite element model of an experiment model. Then these trained neural networks are examined with data obtained from impulse tests on the experiment model. The experiment results show that the trained neural networks are able to detect the damaged member with reasonable accuracy. |
| |
| Keywords: | damage detection offshore platform probabilistic neural networks back-propagation neural networks |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
| 点击此处可从《中国海洋工程》浏览原始摘要信息 |
| 点击此处可从《中国海洋工程》下载免费的PDF全文 |
