0
  • DE
  • EN
  • FR
  • International Database and Gallery of Structures

Advertisement

Calculation of influence line using regular traffic for improving bridge weigh-in-motion under variable vehicle speed

 Calculation of influence line using regular traffic for improving bridge weigh-in-motion under variable vehicle speed
Author(s): , ,
Presented at IABSE Congress: Resilient technologies for sustainable infrastructure, Christchurch, New Zealand, 3-5 February 2021, published in , pp. 366-373
DOI: 10.2749/christchurch.2021.0366
Price: € 25.00 incl. VAT for PDF document  
ADD TO CART
Download preview file (PDF) 0.2 MB

In this study, an influence line of girder deflection of the bridge was calculated for the initial calibration of Bridge Weigh-in-Motion (B-WIM). The deflection responses were obtained from the pro...
Read more

Bibliographic Details

Author(s): (Tokyo Institute of Technology, School of Environment and Society, Tokyo, JAPAN)
(University of Yamanashi, Graduate School of Engineering, Yamanashi, JAPAN)
(University of Yamanashi, Graduate School of Engineering, Yamanashi, JAPAN)
Medium: conference paper
Language(s): English
Conference: IABSE Congress: Resilient technologies for sustainable infrastructure, Christchurch, New Zealand, 3-5 February 2021
Published in:
Page(s): 366-373 Total no. of pages: 8
Page(s): 366-373
Total no. of pages: 8
DOI: 10.2749/christchurch.2021.0366
Abstract:

In this study, an influence line of girder deflection of the bridge was calculated for the initial calibration of Bridge Weigh-in-Motion (B-WIM). The deflection responses were obtained from the proposed integration process using the baseline correction. Optical flow analysis was applied using a video camera to adapt to the variable vehicle speed and precisely measure the location of vehicles on a bridge. A foreground mask using the Gaussian mixture model and a Kalman filter was then applied to identify the vehicles. A calibration process of B-WIM was proposed using the iteration process to optimize the influence line of deflection using local buses in regular traffic. Finally, the axle weights of a weight-known test truck were analyzed by monitoring with the video camera and acceleration sensor. Compared with conventional B-WIM methods, the proposed method has demonstrated higher adaptability in variable vehicle speed.

Keywords:
bridge bridge weigh-in-motion numerical integration optical flow variable speed