考虑环境因素影响的动态法桥梁损伤识别

如何考虑因环境条件变化而引起的结构动力特性的变异性是动态法桥梁损伤识别中的一个难点.文中利用非线性主成分分析技术,提出一种新的桥梁结构损伤识别方法.首先通过构建自联想神经网络对无损结构在不同环境条件下识别得到的单元刚度样本集作非线性主成分分析,建立反映环境因素影响的非线性变换模式.然后,将未知状态结构在不同环境条件下识别得到的单元刚度样本集输入所构建的网络,通过对网络输出与目标间的网络输出残差作统计分析,实现损伤识别与定位.最后以一座简支梁桥为例进行数值仿真分析,验证了所提出方法的有效性.

Vibration-Based Damage Detection of Bridges Considering Influence of Changing Environment

In the vibration-based damage detection of bridges, it is difficult to avoid the uncertainty of the dynamic behaviour caused by changing environmental conditions.In order to overcome this difficulty,a novel damage detection methodology for bridges is proposed based on the nonlinear principal component analysis.In this methodology,first,an auto-associative neural network is constructed to carry out a nonlinear principal component analysis for the element stiffness samples identified from healthy structure in various environmental conditions,and a nonlinear transformation mode that reveals the environmental influences is created.Then,the element stiffness samples obtained from an unknown state in various environmental conditions are inputted into the constructed network.Thus,damages can be detected and located via the statistical analysis of the residual errors between the network outputs and the targets.The proposed methodology is finally verified by the numerical simulation of a simply-supported bridge.