Abstract
Nowadays, the high rate GNSS (Global Navigation Satellite Systems) positioning methods are widely used as a complementary tool to other geotechnical sensors, such as accelerometers, seismometers, and inertial measurement units (IMU), to evaluate dynamic displacement responses of engineering structures. However, the most common problem in structural health monitoring (SHM) using GNSS is the presence of surrounding structures that cause multipath errors in GNSS observations. Skyscrapers and high-rise buildings in metropolitan cities are generally close to each other, and long-span bridges have towers, main cable, and suspender cables. Therefore, multipath error in GNSS observations, which is typically added to the measurement noise, is inevitable while monitoring such flexible engineering structures. Unlike other errors like atmospheric errors, which are mostly reduced or modeled out, multipath errors are the largest remaining unmanaged error sources. The high noise levels of high-rate GNSS solutions limit their structural monitoring application for detecting load-induced semi-static and dynamic displacements. This study investigates the estimation of accurate dynamic characteristics (frequency and amplitude) of structural or seismic motions derived from multipath-affected high-rate GNSS observations. To this end, a novel hybrid model using both wavelet-based multiscale principal component analysis (MSPCA) and wavelet transform (MSPCAW) is designed to extract the amplitude and frequency of both GNSS relative- and PPP- (Precise Point Positioning) derived displacement motions. To evaluate the method, a shaking table with a GNSS receiver attached to it, collecting 10 Hz data, was set up close to a building. The table was used to generate various amplitudes and frequencies of harmonic motions. In addition, 50-Hz linear variable differential transformer (LVDT) observations were collected to verify the MSMPCAW model by comparing their results. The results showed that the MSPCAW could be efficiently used to extract the dynamic characteristics of noisy dynamic movements under seismic loads. Furthermore, the dynamic behavior of seismic motions can be extracted accurately using GNSS-PPP, and its dominant frequency equals that extracted by LVDT and relative GNSS positioning method. Its accuracy in determining the amplitude approaches 91.5% relative to the LVDT observations.
Highlights
The relative and precise point positioning (PPP) GNSS techniques have been intensively developed and used in structural health monitoring and detection of crustal movement applications [1,2,3,4].By using high-rate sampling, amplitudes and frequencies of strong movements can be accurately detected in the position and frequency domains
The re-sampling of 10 Hz linear variable differential transformers (LVDT) is shown in the top panel, and the detrend relative and PPP GNSS results are presented in the bottom panel
It can be noted that the displacements and frequencies obtained from LVDT can be effectively used as a reference value for evaluating the displacement measured using GNSS devices since the amplitudes and frequencies of the four events are approximately the same with the generated motions properties, which are 0.5 Hz/15 mm, 1 Hz/5 mm, 1 Hz/10 mm, and 1 Hz/15 mm for the events 1, 2, 3, and 4, respectively
Summary
The relative and precise point positioning (PPP) GNSS techniques have been intensively developed and used in structural health monitoring and detection of crustal movement applications [1,2,3,4].By using high-rate sampling, amplitudes and frequencies of strong movements can be accurately detected in the position and frequency domains. The relative and precise point positioning (PPP) GNSS techniques have been intensively developed and used in structural health monitoring and detection of crustal movement applications [1,2,3,4]. Li [5] evaluated the accuracy of the PPP technique for monitoring seismic motion using an integration method and compared its results with accelerator measurements, and it was realized that a few centimeters accuracy could be obtained for the displacement waveforms and permanent coseismic offsets. Alcay et al [1] compared PPP solutions with relative GNSS positioning considering different session lengths (24, 12, 8, 4, and 2 h) for monitoring permanent (static) displacement in the horizontal and vertical directions
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