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xShake: Intelligent wireless system for cost-effective real-time seismic monitoring of civil infrastructure

  • Fu, Yuguang (School of Mechanical Engineering) ;
  • Hoang, Tu (Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign) ;
  • Mechitov, Kirill (Department of Computer Science, University of Illinois at Urbana-Champaign) ;
  • Kim, Jong R. (Department of Civil and Environmental Engineering, Nazarbayev University) ;
  • Zhang, Dichuan (Department of Civil and Environmental Engineering, Nazarbayev University) ;
  • Spencer, Billie F. Jr. (Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign)
  • 투고 : 2020.08.13
  • 심사 : 2021.07.28
  • 발행 : 2021.10.25

초록

Seismic structural health monitoring (SHM) of structures is critical not only to detect earthquakes to send early warning, but also to enable rapid structural condition assessment to ensure safety. Traditional monitoring systems using wired sensors are expensive. Wireless sensors offer tremendous opportunity to reduce costs, which remains elusive for seismic structural monitoring due to two main obstacles. First, there are constraints on power resources. Most wireless sensors are duty-cycled to preserve limited battery power; and hence, can miss an earthquake in power-saving sleep mode. Second, there is a lack of support for rapid post-event data collection and processing. Conventional data transmission after sensing can introduce significant delays, and real-time data acquisition that eliminates these delays has limited throughput. In this paper, an intelligent wireless monitoring system, xShake, is developed for cost-effective real-time seismic SHM. It consists of: 1) energy-efficient wireless sensor prototypes utilizing on-demand sensing technique, 2) live-streaming framework that supports high-throughput real-time data acquisition, and 3) a rapid condition assessment application, enabling real-time data visualization and processing for end users. The performance of the xShake is validated through lab tests, demonstrating that it can capture high-fidelity synchronized data under earthquakes and enable real-time structural condition assessment.

키워드

과제정보

The authors gratefully acknowledge the support of this research by NSF SBIR under Grant #1913947, Nazarbayev University Research Fund under Grant #SOE2017003, ZJU-UIUC Institute Research under Grant #ZJU083650, Federal Railroad Administration under Grant #DTFR53-17-C00007, and the China Scholarship Council.

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