Monitoring-based assessment of bridges subject to ship collision

Abstract

The bridges over waterways are exposed to ship collision. The risk of ship-bridge collision is increasing due to the increase in the frequency of commercial ship trips in modern times. There are hundreds of ship-bridge collision accidents worldwide every year. Rather than causing the collapse of whole bridges, this kind of accidents usually leads to invisible structural damage, which is well hidden behind an apparent structural integrity condition and may bring about hidden danger threatening the bridge safety. As a result, post-collision condition/damage assessment for ship-collided bridges is of great importance when deciding whether to close a bridge to traffic and when planning consequent bridge retrofitting. The work described in this thesis is devoted to developing a sensor placement optimization method targeting post-collision damage detection of bridges and a set of Hilbert-Huang transform (HHT) based procedures for ship-bridge collision accident alarming and condition/damage assessment of the collided bridges using the monitoring data. On-line structural health monitoring (SHM) systems provide a unique approach to monitor bridge responses during ship collisions and detect the structural damage. The damage information contained in the monitoring data, which is critical for damage detection, however, is largely dependent on the sensor layout. Therefore, an optimal sensor placement method targeting post-collision damage detection of bridges is proposed for selecting the optimal sensor set so that the measured data are most informative for damage detection. The sensor configuration is optimized by a multi-objective optimization algorithm which simultaneously minimizes the information entropy index for each possible ship-bridge collision scenario. One advantage of the proposed method is that it can handle the uncertainty of ship collision position. It also guarantees a redundancy of sensors for the most informative regions, and leaves some freedom to determine the critical elements for monitoring. The proposed method is applicable in practice to determine the sensor placement, prior to field testing, with the intention of identifying post-collision damage. The cable-stayed Ting Kau Bridge in Hong Kong is employed to demonstrate the feasibility and effectiveness of the proposed method. It is promising to detect ship-bridge collision accidents and assess post-collision condition using the monitoring data acquired by SHM systems for the instrumented bridges. The ship-collision-induced bridge dynamic responses are transient, non-stationary and possibly non-linear. In considering the superiority of HHT in representing non-linear and non-stationary signals without any artefacts imposed by the non-locally adaptive limitations of the fast Fourier transform (FFT) and wavelet processing, a set of HHT based techniques is developed for the ship-bridge collision accident detection and ship-collided bridge condition assessment by use of the monitoring data. Firstly a viable accident alarming method based on the original HHT is developed to enhance the accuracy of ship collision accident alarming. Subsequently, a hybrid HHT based approach, which combines the empirical mode decomposition (EMD), FFT, band-pass filter and Hilbert transform, is proposed to interpret the condition of ship-collided bridges. The instantaneous frequencies and transient energy distributions of the collision-induced responses reflected by the resultant Hilbert transform are analyzed in the time-frequency domain, and are compared with the traditional power spectral densities obtained by the FFT and those by the wavelet transform. The measured acceleration responses of the suspension Jiangyin Bridge during a ship collision event are used to testify the effectiveness of the HHT based procedures in alarming the ship-bridge collision accident and assessing the ship-collided bridge condition. The results show that the intrinsic mode functions obtained by the HHT do signal the accident clearer and more accurate than the raw signals, and the hybrid HHT based approach is effective in detecting the structural damage incurred during ship collision.