基于神经网络和滤波技术的贮仓结构参数识别  

Parameter identification of silo using neural network and Kalman filter algorithms

作　　者：董清华[1] 黄义[1] 

机构地区：[1]西安建筑科技大学土木工程学院,陕西西安710055

出　　处：《世界地震工程》2005年第3期116-121,共6页World Earthquake Engineering

摘　　要：利用神经网络和Kalman滤波技术,提出了一种直接识别结构物理参数的方法,用Kalman滤波技术训练网络。在贮仓振动台实验的基础上,用贮仓在动载作用下的位移、速度作为网络的输入,激振加速度和响应加速度作为网络的输出。仿真计算表明,本文方法是可行的。A method to identify the physical parameters of structure system has been developed by using neural network. The Kalman filtering technique is applied to modify the weight matrices of neural network. Based on the shaking table test,we compose a neural network in which the input signals are the response displacement and velocity of the silo, and output signals are the response acceleration of the silo plus input acceleration of the shaking table at time step t . Results from computer simulation studies show that this method is valid and feasible.

关 键 词：识别 神经网络 KALMAN滤波 

分 类 号：P315[天文地球—地震学]