Abstract This study presents a new approach for identification of aerodynamic damping of tall buildings from stochastic crosswind response time history using unscented Kalman filter (UKF) technique. The system damping ratio is expressed as a polynomial function of building displacement or velocity, which is equivalent to a polynomial function of amplitude of harmonic motion. The structural system with nonlinear system damping under stochastic excitation is modeled as a single degree of freedom system with a white noise input. The augmented state variables of the system, which also include unknown system frequency, damping and stochastic excitation parameters, are estimated simultaneously with the UKF technique from the response measurement data. The aerodynamic damping is then extracted from the system damping by subtracting the structural damping. Firstly, the stochastic response time histories of a tall building model at various wind speeds with a known nonlinear aerodynamic model are simulated and the performance of the UKF technique and the influence of selections of various parameters involved are investigated. Secondly, the aerodynamic damping of a square-shaped tall building is identified based on aeroelastic building model wind tunnel test data. The response statistics are then computed using the identified damping and compared with the measurement data to verify the accuracy of identification.

中文翻译：

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使用无迹卡尔曼滤波技术识别高层建筑随机侧风响应的非线性气动阻尼

摘要 本研究提出了一种使用无迹卡尔曼滤波器 (UKF) 技术从随机侧风响应时间历史中识别高层建筑气动阻尼的新方法。系统阻尼比表示为建筑物位移或速度的多项式函数，相当于简谐运动幅度的多项式函数。在随机激励下具有非线性系统阻尼的结构系统被建模为具有白噪声输入的单自由度系统。系统的增强状态变量，还包括未知的系统频率、阻尼和随机激励参数，是通过响应测量数据与 UKF 技术同时估计的。然后通过减去结构阻尼从系统阻尼中提取空气动力学阻尼。首先，用已知的非线性空气动力学模型模拟了高层建筑模型在各种风速下的随机响应时间历程，并研究了 UKF 技术的性能和所涉及的各种参数选择的影响。其次，基于气动弹性建筑模型风洞试验数据对方形高层建筑的气动阻尼进行识别。然后使用识别的阻尼计算响应统计数据并与测量数据进行比较以验证识别的准确性。基于气动弹性建筑模型风洞试验数据识别方形高层建筑的气动阻尼。然后使用识别的阻尼计算响应统计数据并与测量数据进行比较以验证识别的准确性。基于气动弹性建筑模型风洞试验数据识别方形高层建筑的气动阻尼。然后使用识别的阻尼计算响应统计数据并与测量数据进行比较以验证识别的准确性。