Integration of structural health monitoring and intelligent transportation systems for bridge condition assessment: Current status and future direction

Sakib Mahmud Khan, Sez Atamturktur, Mashrur Chowdhury, Mizanur Rahman

Research output: Contribution to journalArticlepeer-review

26 Scopus citations

Abstract

Recent catastrophic bridge failures clearly indicate the urgent need for improving interval-based bridge inspection procedures that are qualitative and subjective in nature. Structural Health Monitoring (SHM) can mitigate the deficiencies of interval-based inspection techniques and provide real-time diagnostic information regarding the bridge structural health. SHM is not flawless however; the variability in the vehicle characteristics and traffic operational conditions makes it prone to false diagnosis. Recent advancements in the integration of SHM with intelligent transportation systems (ITS) demonstrate the successful use of ITS devices (e.g., traffic cameras, traffic detectors) in the analysis of bridge responses to multimodal traffic with varying loads or during the critical events that cause excess vibration beyond the normal limit. In an ITS-informed SHM system, the ITS device collected data can be integrated with SHM to increase the reliability and accuracy of the SHM system. This integration would reduce the possibility of false diagnosis of damages detected by the SHM system (e.g., vibrations caused by heavy vehicles on a bridge could be read by a SHM sensor as a structural health problem of the bridge), which would eventually decrease the bridge maintenance costs. Similarly, in SHM-informed ITS system, SHM sensors can provide data on bridge health condition for ITS applications, where ITS uses this bridge health condition information for real-time traffic management. In this paper, literature related to both ITS-informed SHM and SHM-informed ITS is reviewed. Based on the literature review, potential challenges and future research directions associated with ITS-SHM integration are also discussed.

Original languageEnglish (US)
Article number7422072
Pages (from-to)2107-2122
Number of pages16
JournalIEEE Transactions on Intelligent Transportation Systems
Volume17
Issue number8
DOIs
StatePublished - Aug 2016

All Science Journal Classification (ASJC) codes

  • Automotive Engineering
  • Mechanical Engineering
  • Computer Science Applications

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