Civil infrastructure is very much exposed to ageing. With an extensive construction boom during several periods in the past a large number of bridges, roads, buildings and other type of infrastructure exist, which is reaching a stage of increased deterioration. Damage is a stochastic process to a certain degree which is gradually progressing. The earlier damage can be monitored the better a building can be managed in terms of maintenance and thus life cycle cost. Non‐destructive testing (NDT) is still a very new area of science in civil engineering dating back to the mid 1980ies only. Challenges have to be seen with the size of the components to be monitored as well as some of the fairly complex materials to be used such as reinforced concrete. Many of the monitoring approaches developed only operate successfully when fusing data obtained from different NDT techniques. Detailed monitoring however also requires a significant amount of work which may only be achieved through automation of the monitoring process. Starting from status quo in infrastructure management different robotic techniques for infrastructure management will be presented as a means of future infrastructure management system that does allow a paradigm shift in future infrastructure management. Examples will include scanners that do monitor reinforced concrete structures on a multi parameter basis, micro aerial vehicles that scan complete buildings visually allowing buildings to be reconstructed in 3D at very high resolution or pipeline inspection gauges (PIGs) allowing pipes to be inspected over hundreds of kilometers autonomously. A further option in monitoring civil infrastructure exists with the integration of sensing devices into structures. Examples to be discussed will be wind energy turbine blades and all the challenges around the subject of wind energy structures and the benefits of monitoring. As a conclusion the idea of damage tolerant design will be addressed which is popular with regard to aeronautical structures but is still a paradigm shift when considering civil engineering infrastructure.
In this presentation, monitoring for long-term performance and wind effects of bridges is included. First, compressive sampling of structural health monitoring data by using the compressive sensing theory is first presented. Then the recovery approach of loss data for wireless sensors network is proposed by using the compressive sensing theory. The identification approach of weight and spatial distribution of vehicles based on tension force of cables using compressive sensing theory is proposed, followed by the identification of real-time variant tension force using Kalman filter based on the monitored acceleration of cables. In addition, the vehicle loads are also statistically obtained using the monitored data and then the extreme value of the vehicle loads is further derived. The second part of this paper is the monitoring for wind and vortex-induced vibration and buffeting of a long-span suspension bridge, and the Reynolds number effects are observed. The software for data analysis and mining of structural health monitoring is shown and the specifications of design for structural health monitoring systems in China are introduced. Finally, the challenge issues emerging from practice of structural health monitoring are summarized.
In the first topic, flexural wave propagation along a long cable is discussed. The governing equation of this phenomenon is the equation of motion for the beam. Flexural waves are one type of dispersive waves, and they can be observed when long cables collide each other. After propagating over a long distance, the impulsive wave becomes a continuous sinusoidal wave and its period changes from high frequency to low frequency. This means that the propagation speed of the flexural wave is a function of frequency. The second topic is how to estimate the cable tension from vibration tests. As you know, cable tension is a very important parameter in the design and maintenance of a bridge. Consider the equation of motion for a beam in tension. Tension and bending rigidity are the coefficients of the partial differential equation that models the behavior of the beam. By determining, through experiments, several of a tensioned cable’s resonance frequencies, it will be shown that it is theoretically possible to use those frequencies to estimate the coefficients of the differential equation, i.e., the tension and bending rigidity.