基于ACVMD-WT法的GNSS-RTK高耸结构动态监测与模态分析

Dynamic monitoring and modal analysis of the high-rise structure by GNSS-RTK based on ACVMD-WT method

为对高耸结构的安全性能进行评估,采用GNSS-RTK技术对天津广播电视塔进行动态监测。对监测误差及噪声进行分析,基于变分模态分解(variational modal decomposition,VMD)和小波阈值(wavelet threshold,WT)提出了ACVMD-WT算法。通过模拟信号验证了VMD比添加自适应噪声的完备集合经验模态分解(complete ensem-ble empirical mode decomposition with adaptive noise,CEEMDAN)的信号重组能力更强。利用所提算法对水平方向信号进行降噪并得到结构的模态参数。结果表明:水域环境易引起背景噪声,对监测结果产生不利影响;ACVMD-WT滤波实现了对信息分量的有效筛选,降噪前后信号具有较强的相关性;相比集合经验模态分解(en-semble empirical mode decomposition,EEMD),CEEMDAN以及CEEMDAN-WT,所用算法的降噪效果更佳;由降噪后信号更好地获取到结构的前三阶频率及阻尼信息,其中一阶频率与有限元分析的相对误差为0.189%,第三阶频率相对误差最大值仅为4.054%,提高了模态频率辨识度和准确度。

To evaluate the safety performance of the high-rise structure,GNSS-RTK technology is applied for the dynamic moni-toring of Tianjin radio and television tower.The monitoring errors and noise are analyzed.An ACVMD-WT algorithm is proposed based on variational modal decomposition(VMD)and wavelet threshold(WT).The simulation signal verifies that VMD has su-perior signal reorganization ability than the complete ensemble empirical mode decomposition with adaptive noise(CEEMDAN).The algorithm adopted is used to denoise the horizontal signals and obtain the structural modal parameters.The results show that the water environment is prone to generate background noise,which adversely affects the monitoring result.The information com-ponents are selected effectively by ACVMD-WT mixed filter,and the signals before and after noise reduction have a strong correla-tion.In contrast to the ensemble empirical mode decomposition(EEMD),CEEMDAN,and CEEMDAN-WT,the method used has a better noise reduction effect.The first three-order frequencies and damping information of the structure are better captured from the noise reduction signal,the relative error of the first-order frequency with the finite element analysis is 0.189%,and the maximum value of the third-order frequency relative error is only 4.054%,improving the recognition and accuracy of the modal fre-quency.