Research on the defect determination of large-span steel structure based on neural network
Xiong Zhong-ming1; Wang Chao1; Lin Tao2
Xi’an University of Architecture and Technology civil engineering college Shaanxi Xi’an 710055;Tangshan Planning and Architecture Design Research Institute Hebei Tangshan 063000
Abstract：Large-span steel structure has been widely used in large-scale public buildings such as stadiums in recent years. But the location of defects has not been solved well which will affect the safety in the using process. In the background of the large span steel structure of a college stadium, a simulating study on the location of the defect based on neural network was put forward, the modal parameter before and after the structural damage was obtained from ANSYS model analysis of the large span steel structure, and which is taken as input parameter of the neural network. In order to improve the convergent speed and the diagnostic accuracy of the network model for the structural defects, when locating the structural damage, on one hand, the structure subdivided into a large amount of sub-structure and narrow the damage scope; on the other hand, input high frequency into different experimental samples of the neural network to conduct experiments to detect the influence of the damage location and damage degree caused by it. The results showed that the technology of neural network for the defects location of large complex structure was feasible, and the identification accuracy was greatly enhanced by improving the method, it will provide a meaningful reference for network improvements and improving the accuracy, interference immunity and generalization ability of neural network
熊仲明;王超;林涛. 基于神经网络的大跨钢结构缺陷损伤的定位研究[J]. , 2011, 30(9): 191-196.
Xiong Zhong-ming;Wang Chao;Lin Tao. Research on the defect determination of large-span steel structure based on neural network. , 2011, 30(9): 191-196.
2011, Vol. 30 
