摘要
对简支梁进行了损伤分析,研究了不同损伤工况下的频率变化率和模态振型曲率变化,并采用径向基神经网络对结构进行了损伤识别研究,研究中采用了三种方案:仅利用频率变化率;仅用第1阶模态曲率变化;综合使用前3阶频率变化率和模态曲率变化。结果表明,基于动力参数和径向基神经网络的结构损伤识别方法能够准确地识别结构的损伤程度;神经网络的输入参数选择对结果有较大影响,综合使用频率变化率和模态曲率变化的第3种方案识别效果最好。
Damage analysis of simply supported beam is presented in this paper,involving rate of frequency change and change of mode shape curvature at different kinds of scenarios.RBF neural networks are adopted to identify the structural damage.Three schemes,which choose different parameters as input of networks,are used in the damage identification process：（1） only rate of frequency change;（2） only the first order mode shape curvature change;（3） the combination of the first three orders of rate of frequency change and change of mode shape curvature.Results show that the structural damage can be identified by using RBF networks and vibration characters,and the input parameters of networks do the bigger inf-luence on the identification effect.The combination scheme（3） makes the best results in this paper.
出处
《公路》
北大核心
2011年第5期56-61,共6页
Highway
关键词
损伤识别
频率
模态曲率
径向基网络
damage identification
frequency
mode curvature
RBF network
