TY - JOUR
T1 - Integration of structural health monitoring and intelligent transportation systems for bridge condition assessment
T2 - Current status and future direction
AU - Khan, Sakib Mahmud
AU - Atamturktur, Sez
AU - Chowdhury, Mashrur
AU - Rahman, Mizanur
N1 - Publisher Copyright:
© 2000-2011 IEEE.
PY - 2016/8
Y1 - 2016/8
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84960145846&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84960145846&partnerID=8YFLogxK
U2 - 10.1109/TITS.2016.2520499
DO - 10.1109/TITS.2016.2520499
M3 - Article
AN - SCOPUS:84960145846
SN - 1524-9050
VL - 17
SP - 2107
EP - 2122
JO - IEEE Transactions on Intelligent Transportation Systems
JF - IEEE Transactions on Intelligent Transportation Systems
IS - 8
M1 - 7422072
ER -