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Identification of dynamic displacements and modal frequencies of amedium-span suspension bridge using multimode GNSS processing

机译:利用多模GNSS处理识别中跨悬索桥的动态位移和模态频率

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摘要

Global Navigation Satellite System (GNSS) positioning technology has been employed in the dynamic monitoring of long-span bridges in the recent years. However, it has difficulties to meet the higher accuracy requirements of the dynamic monitoring of small or medium span bridges, due to the presence of measurement noise from multipath, cycle slips, ionosphere delay, orbital errors, etc. To verify the feasibility of using current GNSS technology to monitor these bridges, a series of monitoring experiments have been carried out on the Wilford suspension bridge in Nottingham (UK) with GNSS and a triaxial accelerometer. Three GNSS data processing modes, i.e. Real-Time Kinematic (RTK), network RTK and Post-Processing Kinematic (PPK), were considered. An innovative multimode adaptive filtering (MAF) that combining adaptive filter with Chebyshev highpass filter was used to identify the dynamic displacements of the bridge from the multimode GNSS data. To validate the GNSS results, the dynamic displacements were also computed from double integration of the accelerometer-measured accelerations. The differences of the displacements between the GNSS and accelerometer results were obtained. The standard deviation and the mean deviation of these differences are less than 1 mm, which is good enough for the monitoring purposes. The modal frequencies of the bridge can be accurately identified from GNSS measurements, and successfully validated by those from the accelerometer data. Using the multimode GNSS data and the proposed the MAF algorithm, with sub-millimeter level accuracy GNSS can be used to monitor the vibration response of small or medium span bridges as well as long-span bridges.
机译:近年来,全球导航卫星系统(GNSS)定位技术已用于大跨度桥梁的动态监测。但是,由于存在多径,周跳,电离层延迟,轨道误差等引起的测量噪声,因此难以满足中小型跨桥动态监测的更高精度要求。验证使用电流的可行性GNSS技术用于监视这些桥梁,已经在英国诺丁汉的Wilford悬索桥上使用GNSS和三轴加速度计进行了一系列监视实验。考虑了三种GNSS数据处理模式,即实时运动(RTK),网络RTK和后处理运动(PPK)。将自适应滤波器与Chebyshev高通滤波器相结合的创新型多模自适应滤波(MAF)用于从多模GNSS数据中识别桥梁的动态位移。为了验证GNSS结果,还通过对加速度计测得的加速度进行两次积分来计算动态位移。得到了GNSS和加速度计结果之间位移的差异。这些差异的标准偏差和平均偏差小于1 mm,足以用于监视目的。可以从GNSS测量中准确识别出桥梁的模态频率,并通过加速度计数据成功地验证了模态频率。使用多模GNSS数据和提出的MAF算法,具有亚毫米级别的精度,GNSS可以用于监视中小跨度桥梁以及大跨度桥梁的振动响应。

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