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.
The detection of damage in structures at its earliest stages has many economical and safety benefits. Permanent monitoring systems using various forms of sensor networks and analysis methods are often employed to increase the frequency and diagnostic capabilities of inspections. Some of these techniques provide spatial/volumetric information about a given area/volume of a structure. Many of the available spatial sensing techniques can be costly and cannot be permanently deployed (e.g., IR camera thermography). For this reason intricate analysis methods using permanently deployable sensors are being developed (e.g., ultrasonic piezoelectrics, sensing skins). One approach is to leverage the low cost of heaters and temperature sensors to develop an economical, permanently installable method of spatial damage detection using heat transfer. This paper presents a method similar to that of X-ray computed tomography (CT). However, the theories for Xray CT must be adapted to properly represent heat transfer as well as account for the relatively large and immobile sensors spacing used on a structure (i.e., there is a finite number of heaters/sensors permanently installed around the perimeter of the area of interest). The derivation of heat transfer computed tomography is discussed in this paper including two methods for steering the effective heat wave. A high fidelity finite element method (FEM) model is used to verify the analytical derivation of individual steps within the method as well as simulate the complete damage detection technique. Experimental results from both damaged and undamaged aluminum plate specimens are used to validate the FEM model and to justify theoretical assumptions. The simulation results are discussed along with possible improvements and modifications to the technique.