改进贝叶斯谱密度法及其在超高层结构振动模态参数识别中的应用

Modified Bayesian spectral density approach and its application to modal parameter identification of super-tall building

基于白噪声激励的贝叶斯谱密度识别方法,可在识别出结构模态参数的同时,对识别结果的不确定性进行评估。在贝叶斯谱密度法(BSDA)的基础上,进一步提出适合有色噪声激励的改进参数识别方法(MBSDA),并对参数已知的合成信号进行参数识别。通过两种方法识别出的阻尼比、荷载等主要参数指标的对比表明,MBSDA比BSDA有较高的准确性。对位于深圳市高280 m的超高层建筑在近5年4次台风作用下的加速度响应时程进行参数识别,并评估结果的不确定性。结果表明:采用MBSDA和BSDA对结构频率进行识别,二者结果基本一致,但前者识别得到的模态阻尼比略高于后者;由4次台风作用下的加速度响应识别得到的阻尼比和结构振动加速度均方根之间不存在明显的统计相关性,所测超高层建筑的平均阻尼比为1.02%。

The Bayesian spectral density identification method based on the assumpuon ,, w,,l~ obtain the modal parameters of the structure as well as their uncertainties. Based on the Bayesian spectral density approach （BSDA）, the Modified Bayesian spectral approach （MBSDA） was developed, which allowed the identification of colored noise excitation. The proposed method and the conventional BSDA were applied to modal parameter identification of synthetic signal with fixed parameters. Comparisons of identified damping ratios, load and other parameters show that MBSDA has a higher accuracy than BSDA. Then, modal parameter identification was performed on a 280 m high super-tall building in Shenzhen using the acceleration response under four strong winds in recent five years, during which uncertainties of identified values were also evaluated. It is found that identified natural frequencies agree well but the identified modal damping ratios of the former are a bit higher. Investigation of the identified damping ratios using full-scale measurement data under four typhoons and windless conditions indicates that the damping ratios do not appear to have an obvious statistical correlation with the root mean square value of acceleration. The average damping ratio of the tested building is 1.02%.