TY - GEN
T1 - Energy-efficient autonomous framework for monitoring railroad bridges in the USA using wireless smart sensors
AU - Spencer, B. F.
AU - Hoang, T.
AU - Mechitov, K. A.
N1 - Publisher Copyright:
© 2021 Taylor & Francis Group, London
PY - 2021
Y1 - 2021
N2 - One of the most critical components of the US transport system is railroads: providing means of transportation for 48% of the nation's total modal tonnage. Despite such important tasks, more than half of the railroad bridges, the essential component of railroads to maintain flow of network, were built before 1920, making them the most fragile components of the railroad system. Wired and wireless sensor systems have been deployed, but none is designed specifically to address the challenges of railroad bridges monitoring, including: 1) limited energy source for sensors; 2) short and random nature of train schedule; 3) unavailable autonomous monitoring systems; and 4) difficult rapid decision-making process due to long data processing time. This paper focuses on efforts to develop an autonomous schedule-based framework for monitoring railroad bridges using wireless smart sensor network (WSSN). This framework, which bases on WSSN platform Xnode, makes use of multiple components, including hardware, software, and algorithms to fulfill the needs for railroad bridge condition monitoring. To demonstrate the efficacy of this system, a full-scale monitoring campaign has been conducted. With these improvements to overcome the challenges of monitoring railroad bridges, this system is expected to become an important tool for railroad engineers and decision makers.
AB - One of the most critical components of the US transport system is railroads: providing means of transportation for 48% of the nation's total modal tonnage. Despite such important tasks, more than half of the railroad bridges, the essential component of railroads to maintain flow of network, were built before 1920, making them the most fragile components of the railroad system. Wired and wireless sensor systems have been deployed, but none is designed specifically to address the challenges of railroad bridges monitoring, including: 1) limited energy source for sensors; 2) short and random nature of train schedule; 3) unavailable autonomous monitoring systems; and 4) difficult rapid decision-making process due to long data processing time. This paper focuses on efforts to develop an autonomous schedule-based framework for monitoring railroad bridges using wireless smart sensor network (WSSN). This framework, which bases on WSSN platform Xnode, makes use of multiple components, including hardware, software, and algorithms to fulfill the needs for railroad bridge condition monitoring. To demonstrate the efficacy of this system, a full-scale monitoring campaign has been conducted. With these improvements to overcome the challenges of monitoring railroad bridges, this system is expected to become an important tool for railroad engineers and decision makers.
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U2 - 10.1201/9780429279119-8
DO - 10.1201/9780429279119-8
M3 - Conference contribution
AN - SCOPUS:85110143497
SN - 9780367232788
T3 - Bridge Maintenance, Safety, Management, Life-Cycle Sustainability and Innovations - Proceedings of the 10th International Conference on Bridge Maintenance, Safety and Management, IABMAS 2020
SP - 91
EP - 99
BT - Bridge Maintenance, Safety, Management, Life-Cycle Sustainability and Innovations - Proceedings of the 10th International Conference on Bridge Maintenance, Safety and Management, IABMAS 2020
A2 - Yokota, Hiroshi
A2 - Frangopol, Dan M.
PB - CRC Press/Balkema
T2 - 10th International Conference on Bridge Maintenance, Safety and Management, IABMAS 2020
Y2 - 11 April 2021 through 15 April 2021
ER -