Analyzing GNSS Measurements to Detect and Predict Bridge Movements Using the Kalman Filter (KF) and Neural Network (NN) Techniques

In this study, we present a data processing framework to apply measurements of the Global Navigation Satellite System (GNSS) technique for analyzing and predicting the movements of civil structures such as bridges. The proposed approach reduces the noise level of GNSS measurements using the Kalman Filter (KF) approach and enables the estimation of static, semi-static, and dynamic components of the bridge’s movements using a series of analyses such as the temporal filtering and the Least Squares Harmonic Estimation (LS-HE). The numerical results indicate that by using a RTK-GNSS system the semi-static component is extracted with a Standard Deviation (STD) of 0.032, 0.048, and 0.06 m in the North, East, and Up (NEU) directions, while that of the dynamic component is 0.004, 0.003, and 0.01 m, respectively. Comparing the dominant frequencies of the bridge movements from LS-HE with those of the permanent stations provides information about the bridge’s stability. To predict its deflection, the Neural Network (NN) technique is tested to simulate the time-varying components, which are then compared with the safety limits, known by its design, to assess the structural health under usual load.

Modeling and Prediction of Regular Ionospheric Variations and Deterministic Anomalies

Knowledge on the ionospheric total electron content (TEC) and its prediction are of great practical importance and engineering relevance in many scientific disciplines. We investigate regular ionospheric anomalies and TEC prediction by applying the least squares harmonic estimation (LS-HE) technique to a 15 year time series of the vertical TEC (VTEC) from 1998 to 2014. We first detected a few new regular and modulated signals in the TEC time series. The multivariate analysis of the time series indicates that there are diurnal, annual, 11 year, and 27 day periodic signals, as well as their higher harmonics. We also found periods matching with the global positioning system (GPS) draconitic year in the TEC time series. The results from the modulated harmonic analysis indicate that there exists a set of peaks with periods of 1 ± 0.0027 j ( j = 1 , … , 5 ) and 1 ± 0.00025 j ( j = 1 , 2 , 3 ) days. The same situation holds also true for the harmonics higher than the diurnal signal. A model is then adopted based on the discovered periods. This model, which consists of pure and modulated harmonic functions, is shown to be appropriate for assessing the regular variations and ionospheric anomalies. There is a clear maximum TEC at around 22:00 h, which we called the “evening anomaly”. The evening anomaly occurs in the winter and autumn, and is dependent on the solar activities. Also, the Semiannual, Winter, and Equatorial anomalies were investigated. Finally, to investigate the performance of the derived model, the TEC values have been predicted monthly, and the results show that the modulated signals can significantly contribute to obtaining superior prediction results. Compared with the pure signals, the modulated signals can improve a yearly average root mean squared error (RMSE) value in the lower and higher solar activities by 20% and 15%, respectively.

Determination of the tide constituents at Livingston and Deception Islands (South Shetland Islands, Antarctica), using annual time series

A detailed study is presented of the tidal constituents for Livingston and Deception Islands (Antarctica) obtained at the LIVMAR and DECMAR tide gauge stations. Data were acquired with tide gauge pressure sensors, and calculated from a long time series of 798 days of data-logging, using the least-squares harmonic estimation method. The results show an improvement over previous results in the region. Seventy tidal constituents were obtained, of which 19 were the most representative with amplitudes greater than 1 cm and a contribution of 93% of the wave energy. In both stations, it was confirmed that the tides are mixed, with a semi-diurnal behavior. The tidal gauge benchmarks (TGBMs) were linked to vertical and horizontal Antarctic Geodetic Networks, which provides a very important contribution for geodetic, oceanographic and hydrographic studies in the area.

Detection of main tidal frequencies using least squares harmonic estimation method

In this paper the efficiency of the method of Least Squares Harmonic Estimation (LS-HE) for detecting the main tidal frequencies is investigated. Using this method, the tidal spectrum of the sea level data is evaluated at two tidal stations: Bandar Abbas in south of Iran and Workington on the eastern coast of the UK. The amplitudes of the tidal constituents at these two tidal stations are not the same. Moreover, in contrary to the Workington station, the Bandar Abbas tidal record is not an equispaced time series. Therefore, the analysis of the hourly tidal observations in Bandar Abbas and Workington can provide a reasonable insight into the efficiency of this method for analyzing the frequency content of tidal time series. Furthermore, applying the method of Fourier transform to the Workington tidal record provides an independent source of information for evaluating the tidal spectrum proposed by the LS-HE method. According to the obtained results, the spectrums of these two tidal records contain the components with the maximum amplitudes among the expected ones in this time span and some new frequencies in the list of known constituents. In addition, in terms of frequencies with maximum amplitude; the power spectrums derived from two aforementioned methods are the same. These results demonstrate the ability of LS-HE for identifying the frequencies with maximum amplitude in both tidal records.