摘要: |
The significance of this study is two-fold. Firstly, it will
demonstrate an application-centric example of ITS and SHM
integration. According to a review on ITS and SHM
integration by Khan et al. [4], few examples exist in the
literature which relate to the estimation of structural features.
These types of applied studies are important to establish
credibility in these techniques as solutions to practical
problems. Secondly, through data fusion techniques, the study
will explore alternative sensing methods to complement
camera-based measurements, which can suffer from poor
performance at night or during inclement weather. A subset of
ITS systems, called Bridge-Weigh-InMotion (BWIM)
systems, have been developed over several decades to
estimate number of axles and vehicle weight using only
contact sensors (no cameras). However, positional tracking
and vehicle classification has not traditionally been part of the
BWIM approach. Furthermore, weight estimation of vehicles
on long bridges like the Varina-Enon has not been commonly
studied for BWIM [3]. The use of complementary ITS
methodologies is a key feature of this study, intended to
improve the long-term reliability of these systems. ITS and
SHM systems have the potential to save highway
infrastructure managers millions in traffic control and
maintenance operations, respectively. However,
implementation of these systems individually by industry has
been slow [4]. The integration of the two systems is more
attractive to practitioners because it brings improved
performance at a lower cost. That is, on one hand, ITS can
make SHM estimates more accurate by providing load
information. On the other hand, SHM can complement ITS
data to help estimate vehicle weights and overcome |