Research of Sensor Fault Identification and Warning in the Urban Bridge Cluster Monitoring System

Bridge structural health monitoring system comprises a variety of sensors for measurement of physical parameters of structure and its surrounding environment. Despite the fact that the data acquisition system is designed by the advanced sensors, the invalid data and sensor fault is unavoidable in the uninterrupted monitoring system. A novel method based on sensor correlation analysis is proposed for identifying continuous invalid data and sensor fault, which were integrated and applied in the project of main roads bridge Online Safety Monitoring Management System in Hangzhou (Phase II), a web-based urban bridge cluster monitoring system. According to a tied arch bridge case studies, the correlation degree between temperature and displacement sensor according to sliding time window is calculated. Simulation results verify the effectiveness of the designed method and the application of the method in the fault identification and warning is discussed.

• Record URL:
  https://doi.org/10.1061/9780784412435.089
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/isbn/9780784412435
• Supplemental Notes:
  • © 2012 American Society of Civil Engineers.
• Corporate Authors:

  American Society of Civil Engineers

  1801 Alexander Bell Drive
  Reston, VA  United States  20191-4400
• Authors:
  • Li, Yi
  • Wei, Hua
• Conference:
  • International Conference On Civil Engineering And Urban Planning 2012
  • Location: Yantai , China
  • Date: 2012-8-12 to 2012-8-20
• Publication Date: 2012-7

Language

• English

Media Info

• Media Type: Digital/other
• Pagination: pp 504-509
• Monograph Title: Civil Engineering and Urban Planning 2012

Subject/Index Terms

• TRT Terms: Arch bridges; Bridges; Sensors; Structural health monitoring; Urban areas
• Uncontrolled Terms: Tied arches
• Subject Areas: Bridges and other structures; Highways; Maintenance and Preservation; I60: Maintenance;

Filing Info

• Accession Number: 01502521
• Record Type: Publication
• ISBN: 9780784412435
• Files: TRIS, ASCE
• Created Date: Nov 12 2013 2:33PM