运营条件下异型拱桥的模态参数识别

发布时间：2018-05-27 23:46

本文选题：运营条件 + 模态参数识别　；参考：《振动.测试与诊断》2014年06期

【摘要】：以一复杂的异型钢管混凝土拱桥为对象,根据运营期间车辆交通荷载引起的余振实侧结果,用小波变换(wavelet transform,简称WT)和特征系统实现法(eigensystem realization algorithm,简称ERA)两种方法对结构模态参数识别结果进行了对比,讨论了两种方法在复杂结构体系模态参数识别中的适用性,进一步以ERA识别方法为对象,比较了记录波除噪及不同记录波对参数识别结果的影响。结果表明:WT方法以及ETA方法得到的结构模态参数识别结果基本一致,两种方法相互校核可剔除噪声模态,获得真实的结构模态信息;除噪对基于余振衰减波的模态参数识别精度提高意义不大,不同记录波的对比识别可剔除单波随机噪声的影响,提高识别结果的可靠性。
[Abstract]:Taking a complicated concrete-filled steel tubular arch bridge as an example, according to the results of residual vibration caused by vehicle traffic load during operation, The identification results of structural modal parameters are compared by wavelet transform and eigensystem realization algorithm, and the applicability of the two methods in modal parameter identification of complex structure system is discussed. Furthermore, the ERA recognition method is used to compare the effects of the noise removal of the recorded wave and the different recorded waves on the parameter identification results. The results show that the identification results of the structural modal parameters obtained by the two methods are basically the same as those obtained by the ETA method. The two methods can eliminate the noise modes and obtain the real structural modal information. Noise removal is of little significance to improve the accuracy of modal parameter identification based on Yu Zhen attenuation wave. The contrast recognition of different recorded waves can eliminate the influence of single wave random noise and improve the reliability of identification results.
【作者单位】：浙江大学土木工程系;浙江大学建筑设计研究院市政交通分院;
【基金】：国家自然科学基金资助项目(50778160)
【分类号】：U446;U448.22

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