دسته بندی:
بینایی ماشین - Machine vision
سال انتشار:
2022
عنوان انگلیسی مقاله:
A computer vision-based method for bridge model updating using displacement influence lines
ترجمه فارسی عنوان مقاله:
یک روش مبتنی بر بینایی کامپیوتری برای بهروزرسانی مدل پل با استفاده از خطوط موثر جابجایی
منبع:
ScienceDirect- Elsevier- Engineering Structures, 259 (2022) 114129: doi:10:1016/j:engstruct:2022:114129
نویسنده:
Alberto Martini
چکیده انگلیسی:
This paper presents a new computer vision-based method that simultaneously provides the moving vehicle’s
tire loads, the location of the loads on a bridge, and the bridge’s response displacements, based on which the
bridge’s influence lines can be constructed. The method employs computer vision techniques to measure the
displacement influence lines of the bridge at different target positions, which is then later used to perform
model updating of the finite element models of the monitored structural system.
The method is enabled by a novel computer vision-based vehicle weigh-in-motion method which the coauthors recently introduced. A correlation discriminating filter tracker is used to estimate the displacements at
target points and the location of single or multiple moving loads, while a low-cost, non-contact weigh-in-motion
technique evaluates the magnitude of the moving vehicle loads.
The method described in this paper is tested and validated using a laboratory bridge model. The system
was loaded with a vehicle with pressurized tires and equipped with a monitoring system consisting of laser
displacement sensors, accelerometers, and cameras. Both artificial and natural targets were considered in the
experimental tests to track the displacements with the cameras and yielded robust results consistent with the
laser displacement measurements.
The extracted normalized displacement influence lines were then successfully used to perform model
updating of the structure. The laser displacement sensors were used to validate the accuracy of the proposed
computer vision-based approach in deriving the displacement measurements, while the accelerometers were
used to derive the system’s modal properties employed to validate the updated finite element model. As a
result, the updated finite element model correctly predicted the bridge’s displacements measured during the
tests. Furthermore, the modal parameters estimated by the updated finite element model agreed well with
those extracted from the experimental modal analysis carried out on the bridge model.
The method described in this paper offers a low-cost non-contact monitoring tool that can be efficiently
used without disrupting traffic for bridges in model updating analysis or long-term structural health monitoring.
keywords: Computer vision | Displacement influence line | Vehicle weigh-in-motion | Structural identification | Finite element method model | Model updating | Modal analysis | Bridge systems
قیمت: رایگان
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