Using weigh-in-motion data to identify traffic loading on a long-span suspension bridge

Yiqing Ni, Y. W. Wang, Y. X. Xia

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

Abstract

This paper presents the identification of highway traffic loading on the suspension Tsing Ma Bridge (TMB) based on the weigh-in-motion (WIM) data collected in 2007. One year of monitoring data is analyzed in terms of vehicle traffic count, vehicle traffic composition, as well as highway loading distribution including axle load distribution and gross vehicle weight (GVW) distribution. The results show that the total vehicles travelling on the TMB are much lower than those specified in the design. The highway load spectra, including both the axle load spectrum and GVW spectrum, are formulated by using the monitoring data, and compared with the load spectrum given in BS5400 and the design load spectrum. The load spectra derived from the WIM data are quite close to those stipulated in BS5400. In particular, both are on the safe side as compared with the design load spectrum.
Original languageEnglish
Title of host publicationSHMII 2015 - 7th International Conference on Structural Health Monitoring of Intelligent Infrastructure
PublisherInternational Society for Structural Health Monitoring of Intelligent Infrastructure, ISHMII
Publication statusPublished - 1 Jan 2015
Event7th International Conference on Structural Health Monitoring of Intelligent Infrastructure, SHMII 2015 - Torino, Italy
Duration: 1 Jul 20153 Jul 2015

Conference

Conference7th International Conference on Structural Health Monitoring of Intelligent Infrastructure, SHMII 2015
Country/TerritoryItaly
CityTorino
Period1/07/153/07/15

ASJC Scopus subject areas

  • Building and Construction
  • Civil and Structural Engineering
  • Artificial Intelligence

Fingerprint

Dive into the research topics of 'Using weigh-in-motion data to identify traffic loading on a long-span suspension bridge'. Together they form a unique fingerprint.

Cite this