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Condition Assessment and Maintenance Strategies for Bridges at Individual and Network Level

 Condition Assessment and Maintenance Strategies for Bridges at Individual and Network Level
Author(s): , , ,
Presented at IABSE Symposium: Tomorrow’s Megastructures, Nantes, France, 19-21 September 2018, published in , pp. S14-33
DOI: 10.2749/nantes.2018.s14-33
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Bridges degenerate due to severe environment, over loading, initial structural defects, disasters or some other factors. How to evaluate and ensure the safety of these structures, at individual lev...
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Bibliographic Details

Author(s): (Tongji University, Shanghai, China)
(Tongji University, Shanghai, China)
(Hebei Transportation Investment Group Corporation, Shijiazhuang, China)
(Hebei Transportation Investment Group Corporation, Shijiazhuang, China)
Medium: conference paper
Language(s): English
Conference: IABSE Symposium: Tomorrow’s Megastructures, Nantes, France, 19-21 September 2018
Published in:
Page(s): S14-33 Total no. of pages: 6
Page(s): S14-33
Total no. of pages: 6
DOI: 10.2749/nantes.2018.s14-33
Abstract:

Bridges degenerate due to severe environment, over loading, initial structural defects, disasters or some other factors. How to evaluate and ensure the safety of these structures, at individual level as well as network level, is a question attracting enough attention. At individual level, this paper proposes the Neutral Axis Indicator (NA) based on strain measurements, to evaluate the performance of an individual bridge and to investigate challenges associated with the neutral axis for structural health monitoring purpose. At network level, a framework is proposed to evaluate bridge groups and to compute the optimal maintenance plan applied to the bridges at a given network. The proposed framework is applied to the bridge network located in Hebei province, China. Results are performed through the data collected from hundreds of bridges over a few years, and the effectiveness and advantages are finally validated.

Keywords:
highway bridge structural health monitoring machine learning Neutral Axis Indicator network level