大跨矮塔斜拉桥模态频率温度影响修正研究

Study on Temperature Effect Correction of Modal Frequency of Long-span Extradosed Cable-stayed Bridge

为修正温度对大跨矮塔斜拉桥模态频率的影响,以G110内蒙古乌海黄河特大桥为研究对象,采用有限元方法得到该桥模态频率理论计算值,基于健康监测系统1年的实测数据,运用NExT-FERA优化算法得到该桥模态频率的实测值.利用主成分分析法提取模态频率中的温度主成分,并通过Matlab构建温度与模态频率之间的回归预测模型,获得模态频率的预测值,再结合理论值和实测值修正温度对模态频率的影响.结果表明:主成分分析法消除了模态频率之间显著的相关性,粒子群算法优化后的SVR模型预测精度更高、计算速度更快,修正温度影响后的模态频率不再跟随季节温度的变化而变化,其标准差大幅降低,验证了PSO-SVR模型对大跨矮塔斜拉桥模态频率温度影响修正的有效性.

In order to correct the influence of temperature on modal frequency of long-span extradosed cable-stayed bridge, G110 Wuhai Yellow River Bridge in Inner Mongolia was taken as the research object, and the theoretical calculation value of modal frequency of the bridge was obtained by finite element method. Based on the measured data of the health monitoring system for one year, the measured modal frequency of the bridge was obtained by using the NExT-FERA optimization algorithm. The principal component analysis method was used to extract the principal component of temperature in modal frequency, and the regression prediction model between temperature and modal frequency was constructed by Matlab, and the predicted value of modal frequency was obtained. Combined with theoretical value and measured value, the influence of temperature on modal frequency was corrected. The results show that the principal component analysis method eliminates the significant correlation between modal frequencies. The SVR model optimized by particle swarm optimization has higher prediction accuracy and faster calculation speed. The modal frequency after the temperature correction no longer changes with the seasonal temperature, and its standard deviation is greatly reduced, which verifies the effectiveness of PSO-SVR model in correcting the temperature effect of modal frequency of long-span extradosed cable-stayed bridge.