GPS-Monitoring and Assessment of Mansoura Railway Steel-Bridge Based on Filter and Wavelet Methods

This study presents Mansoura steel railway bridge, Egypt, movement analysis in response to passing trains. This bridge was used for two types of traffics which are trains on the middle and one vehicle lane on each side of the bridge. A monitoring system is designed based on the Real Time Kinematic Global Positioning System (RTK-GPS) to monitor and assess the bridge behaviour and movements under the effect of trains' loads. Two methods are used to de-noise the GPS data, which are moving average filter (FM) and Wavelet Transform (WT). In addition; the wavelet decomposition is used to classify the noise effects. The time and frequency domain GPS observation analysis results are discussed and the results showed that the bridge is safe under affected train loads in time and frequency domain. Also, it can be concluded that the WT can be used to filter the GPS monitoring data but can't be used to extract the dynamic frequencies. Otherwise, the multiple filters are more suitable method to extract dynamic frequencies for the low sampling GPS frequency instruments.