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Three Integrated Projects to Enhance Non-Contact Rail Inspection Technology for Application to Substructure Health Evaluation on Both Rail and Road Bridges : Final Project Report

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  • English

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    • Alternative Title:
      Final Project Report : Three Integrated Projects to Enhance Non-Contact Rail Inspection Technology for Application to Substructure Health Evaluation on Both Rail and Road Bridges
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    • Abstract:
      Causing loss of use and sometimes life, bridge collapses are always high profile and hit many wallets. The economic benefits of condition-based maintenance are well established, including reduced visual inspection and potentially longer structural life. More accurate estimation of remaining life could potentially prevent collapse but, at a minimum, will aid decision-making on a bridge’s upkeep. This project has extended rail technology towards the generation of an inspection methodology for bridge substructure. Non-destructive optical inspection techniques have been used for assessment of rail structural integrity, but lasers have not been employed for assessment of supporting components underneath the rail. Employing a laser Doppler vibrometer, tiny surface vibrations can be measured that reach into substructural components, including rail ties, bridge deck, piers, footings, and soil. Contact non-destructive testing methods have been used for assessment of structural integrity but only in selected locations, which limits their practicality for inspection of large infrastructure. Due to the size of rail and road bridges, large spacing between test locations can result in poor motion capture and thus missed defects. The non-contact vibrometer overcomes this obstacle, quickly providing measurements at a single location or even while moving. Results are presented for three experimental efforts: a railroad, a scaled reinforced concrete bridge, and an operational on-campus bridge. Traditional cabled accelerometer sensing was used as a basis to determine the feasibility of a vibrometer as an infrastructure inspection tool. The series of experiments reveal that the LDV velocity signals are sensitive enough to use for damage detection in bridges. Once attached to a sturdy base, the moving vibrometer also provided good resonance information despite some slight interference. Limitations include measurement distance and geometrical resolution. In-service traffic excitation is sufficient to provide modal information, and the best case would be multiple large vehicles traversing the bridge at various speeds. Considering noise and sensitivity issues, a structural health evaluation program was developed to efficiently extract modal information and apply multiple health indicators. Modal comparisons between finite element models and processed experimental data show similarities as well as assist in the challenge of coordinating baseline to damaged modes. The program quantitatively contrasts modes to visualize damage level and location, allowing judgments on damage severity and further inspection needs. This achieves the technical aim of identifying global dynamic property changes resulting from local component damage. Civil structures are ideal damage detection applications because they experience incremental changes while aging. On the other hand, the associated signal processing can be extremely challenging due to such low frequency resonances. Field measurements did demonstrate the ability of optical vibrometry to remotely monitor bridge motions, advancing inspection of transportation infrastructure. More research is needed to determine ideal indicators and their “safe” thresholds for various classifications of structures. Enhancing public safety and economic competitiveness, real-time health evaluation and condition-based maintenance are the ultimate aspirations, and a potential product could be a mobile inspection vehicle that would ride along any bridge. The precursory sensitivity studies herein demonstrate that the concept would work: at least one vibrometer on a moving vehicle would be able to provide dynamic bridge data which could then be quickly post-processed to visualize damage level and location. This would indicate that localized inspection and repair action is required before a bridge collapse, for instance.
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