A novel computer vision‐based monitoring methodology for vehicle‐induced aerodynamic load on noise barrier. Issue 12 (3rd October 2018)

• Record Type: Journal Article
• Authors: Pan, Yue; Wang, Dalei; Shen, Xiang; Xu, Yusheng; Pan, Zichao
• Is Part Of: Structural control and health monitoring. Volume 25:Issue 12(2018)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2018-10-03
• Subjects: computer vision -- noise barrier -- numerical simulation -- vehicle identification -- vehicle‐induced aerodynamic load (VIAL); Structural engineering -- Periodicals; Structural control (Engineering) -- Periodicals; Automatic data collection systems -- Periodicals; Detectors -- Periodicals; 624.17
• DOI: 10.1002/stc.2271
• Languages: English
• ISSNs: 1545-2255

Abstract

Summary: Due to the absence of antifatigue design under vehicle‐induced aerodynamic load (VIAL) during the process of structural design, structural failures of noise barriers erected on urban highway viaducts have become a common issue in China. In this paper, a novel VIAL monitoring methodology is proposed, which can achieve a remote VIAL measuring only by analysis and application of the data from a traffic‐monitoring camera. To establish this methodology, a VIAL determinative model and a computer vision system for measuring the vehicle running characteristics are developed. The accuracy and reliability of this methodology have been validated by a field experiment. By comparing with the results of vehicle‐induced aerodynamic pressure (VIAP) from a sensor‐based wind pressure acquisition system, it was found that the systemic root mean square deviations of maximum and minimum values of VIAP were 12.13% and 10.10%, respectively.