节点文献
基于失效树理论的结构多位置损伤检测方法
Method of Multiple Damage Detection in Structures Based on the Failure Tree Theory
【摘要】 在某一确定荷载作用下,结构不同部位的失效概率是不同的。为此提出了基于失效树理论进行人工神经网络样本采集的方法。在此基础上,采用人工神经网络和遗传算法进行结构动力损伤定位和损伤程度的估计。算例分析表明:基于失效树理论可以有效地减少训练样本的大小,从而有效的进行结构多损伤情况下的损伤检测分析。
【Abstract】 Under a specified loading,the failure probability of different element is distinct.So we can get the training sample from the least reliable elements,based on the failure tree of the structures.Then we can apply the ANN and GA to identify the location and the severity prediction of damage.The numerical results of several examples show that failure tree-based sample is feasible for multiple damage detection of large-scale structures.
【关键词】 失效树;
人工神经网络;
遗传算法;
损伤检测;
多位置损伤;
【Key words】 failure tree; artificial neural networks; genetic algorithms; damage detection; multiple damage;
【Key words】 failure tree; artificial neural networks; genetic algorithms; damage detection; multiple damage;
- 【文献出处】 金属世界 ,Metal World , 编辑部邮箱 ,2009年S1期
- 【分类号】TH878
- 【被引频次】1
- 【下载频次】56