| 基于单元应变模态差和RBF神经网络的网架损伤检测方法 |
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| 引用本文： | 张丽梅,刘卫然,张立伟,杜守军,张扬.基于单元应变模态差和RBF神经网络的网架损伤检测方法[J].河北科技大学学报,2013,34(1):79-85. |
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| 作者姓名： | 张丽梅 刘卫然 张立伟 杜守军 张扬 |
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| 作者单位： | 河北科技大学建筑工程学院;中国人民武装警察部队学院基建办公室 |
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| 基金项目： | 河北省教育厅高等学校科学研究计划青年基金项目(2011229,Q2012136);河北科技大学校立科研基金资助项目(XL201234) |
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| 摘 要： | 为对网架进行损伤检测提出应用杆单元应变模态差和RBF神经网络相结合的方法。在ANSYS下建立正放四角锥网架和蜂窝形三角锥网架的有限元模型,采用单元应变模态差作为损伤指标对结构进行杆单元的单杆、多杆损伤位置识别;应用RBF神经网络对杆单元损伤程度进行定量判定。分析结果表明该方法可以比较准确地判断网架杆单元的损伤位置和损伤程度,并对实际网架结构的损伤检测具有一定的指导意义。
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| 关 键 词： | 单元应变模态差 RBF神经网络 网架结构 损伤位置 损伤程度 |
| 收稿时间： | 2012/6/4 0:00:00 |
| 修稿时间： | 2012/10/15 0:00:00 |
Damage testing method of space truss based on elemental strain mode difference and RBF neural network |
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| ZHANG Limei,LIU Weiran,ZHANG Liwei,DU Shoujun and ZHANG Yang.Damage testing method of space truss based on elemental strain mode difference and RBF neural network[J].Journal of Hebei University of Science and Technology,2013,34(1):79-85. |
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| Authors: | ZHANG Limei LIU Weiran ZHANG Liwei DU Shoujun and ZHANG Yang |
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| Institution: | 1.School of Civil Engineering,Hebei University of Science and Technology,Shijiazhuang Hebei 050018,China;2.Construction Office,The Armed Police Academy,Langfang Hebei 065000,China) |
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| Abstract: | Elemental strain mode difference combined with RBF neural network is proposed to detect the damage of space truss structures.Finite element models of square pyramid space truss and honeycomb-shaped triangular pyramid space truss were established.With elemental strain mode difference as criterion,the damage locations of single pole or multi-poles were determined.The damage degrees of the structures were investigated by using RBF neural network.The results show that this method can be used to detect the damage locations and damage degrees of space truss structures. |
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| Keywords: | elemental strain mode difference RBF neural network space truss damage location damage degree |
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