【摘要】 模态参数识别是桥梁风洞试验中的一项重要内容,发展了基于参考点、无需输出协方差估计的识别振动系统模态参数的随机子空间方法,其识别精度和可靠性通过数值算例验证。对状态空间理论中的稳定图作了全面的阐释。根据苏通大桥和苏拉马都大桥主梁三自由度节段模型风洞试验采集到的位移信号,采用随机子空间方法识别了侧弯、竖弯和扭转模态频率和阻尼比,并且与随机搜索方法识别结果进行对比。分析结果表明,随机子空间方法和随机搜索方法识别结果非常吻合,本文发展的随机子空间方法是识别风洞试验桥梁模态参数的一种有效和实用方法。更多还原

【Abstract】 Identification of modal parameters is animportant content forbridge wind tunnel tests.Without output covariance estimation,a reference-based stochastic subspace technique(SST) for identifying modal parameters of vibration system is developed.The identification precision and reliability can be verified via a numerical example.The stabilization diagram involved in the state space theory is comprehensively expounded.Based on the collected displacement signals of 3-DOF sectional models of the Sutong Bridge and the Suramadu Bridge decks in wind tunnel tests,the lateral bending,vertical bending and torsional frequencies and damping ratios are identified using the SST.The analytical results indicate that they are close to those obtained using stochastic search algorithm(SSA).The developed SST is a kind of valid and practical approach for identifying bridge modal parameters in wind tunnel tests.更多还原