12 April 2017 Utilization of wireless structural health monitoring as decision making tools for a condition and reliability-based assessment of railroad bridges
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Abstract
The ability to quantitatively assess the condition of railroad bridges facilitates objective evaluation of their robustness in the face of hazard events. Of particular importance is the need to assess the condition of railroad bridges in networks that are exposed to multiple hazards. Data collected from structural health monitoring (SHM) can be used to better maintain a structure by prompting preventative (rather than reactive) maintenance strategies and supplying quantitative information to aid in recovery. To that end, a wireless monitoring system is validated and installed on the Harahan Bridge which is a hundred-year-old long-span railroad truss bridge that crosses the Mississippi River near Memphis, TN. This bridge is exposed to multiple hazards including scour, vehicle/barge impact, seismic activity, and aging. The instrumented sensing system targets non-redundant structural components and areas of the truss and floor system that bridge managers are most concerned about based on previous inspections and structural analysis. This paper details the monitoring system and the analytical method for the assessment of bridge condition based on automated data-driven analyses. Two primary objectives of monitoring the system performance are discussed: 1) monitoring fatigue accumulation in critical tensile truss elements; and 2) monitoring the reliability index values associated with sub-system limit states of these members. Moreover, since the reliability index is a scalar indicator of the safety of components, quantifiable condition assessment can be used as an objective metric so that bridge owners can make informed damage mitigation strategies and optimize resource management on single bridge or network levels.
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Katherine A. Flanigan, Nephi R. Johnson, Rui Hou, Mohammed Ettouney, Jerome P. Lynch, "Utilization of wireless structural health monitoring as decision making tools for a condition and reliability-based assessment of railroad bridges", Proc. SPIE 10168, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2017, 101681X (12 April 2017); doi: 10.1117/12.2262933; https://doi.org/10.1117/12.2262933
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