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.