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S.L. Desjardins N.A. Londoño and D.T.Lau Ottawa-Carleton Bridge Research Centre

International Collaboration Joint NCREE/JRC Workshop Earthquake Disaster Mitigation Research Methodologies, Facilities, Projects and Networking 17-18 November 2003, Taipei, Taiwan.

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S.L. Desjardins N.A. Londoño and D.T.Lau Ottawa-Carleton Bridge Research Centre

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  1. International Collaboration Joint NCREE/JRC Workshop Earthquake Disaster Mitigation Research Methodologies, Facilities, Projects and Networking 17-18 November 2003, Taipei, Taiwan Implications on the Use of Continuous Dynamic Monitoring Data for Structural Evaluation S.L. Desjardins N.A. Londoño and D.T.Lau Ottawa-Carleton Bridge Research Centre Dept of Civil & Environmental Engineering Carleton University Ottawa, Canada

  2. Overview • Introduction • Objectives • Data processing • SSI System Identification • Verification Study Results • Variability Study • Method & Scope • Data & SSI parameters • Results • Observations & Implications • Real-Time Data Processing and Analysis • Conclusions

  3. Introduction Location of Confederation Bridge

  4. -Confederation Bridge- • 12.9 km long • 100 year design service life • Pre-stressed haunched single box-girder concrete superstructure • 43 main spans of 250 m • 40 m above sea level

  5. -Typical Structural Unit- • Rigid frame (192 m double cantilevers + 52 m rigid drop-in) • 60 m simply supported expansion drop-in

  6. -Dynamics Monitoring- • 76 accelerometers • Data sampling rate: 100 - 167 Hz • Hardware low-pass filter frequency: 50 Hz (anti-aliasing) • Data sample duration: 90 sec - 15 min (inc. 30 sec pre-trigger) • Operation modes: normal mode triggered mode

  7. - Data Transmission -

  8. - Motivations - • Unique structure (length, loads, long service life) • Design assumptions • Verification ofdesign parameters • Structural condition  dynamic properties • Advance towards the use of monitoring data for health monitoring • Ideal setting for research • Utilize data for more efficient operations of the facilities

  9. Objectives • Determine extent of variability of identified properties; • Evaluate feasibility of using monitoring data for condition assessment/health monitoring of the bridge; • Rapid and accurate condition assessment of the monitored structure • continuous basis • extreme events (e.g. wind storm, earthquake, ship impact)

  10. Data Processing • Data checking & repair • Sampling gaps • Data duplication • Baseline adjustment • Low-pass filter • 8th Order Chebyshev Type I, 16.7 Hz cut-off • Data down-sampling

  11. Anti-aliasing hardware filter • 8-pole Bessel Low-Pass Filter • No pass-band ripple • Monotonic roll-off in pass-band & stop-band • Constant delay in pass-band • Low-harmonic distortion

  12. Offline Anti-aliasing Filter 8th Order Chebyshev Type I Low-Pass • Low pass-band ripple • Steep monotonic roll-off • Data filtered in forward and reverse directions to remove all phase distortion

  13. Offline High-Pass Filter 6th order Chebyshev Type II • -60 dB at 0.1 Hz • -0.01 dB at 0.3 Hz • Zero pass-band ripple • Applied in forward and reverse directions to remove phase distortion

  14. Block Hankel Matrix System Identification- Stochastic Subspace Method - Pre-processed data Singular Value Decomposition (SVD) Stochastic state-space model Observability Controllability Data cross-correlationsw.r.t. reference channels Stochastic State-Space Model Matrices Eigenvalue decomposition of A Frequencies Mode Shapes Damping Ratios

  15. Verification Study -Monitoring Data- • Wind-triggered ambient vibration • Truck Traffic induced vibration • Wind storm Nov. 7 2001

  16. Verification Study -Results-

  17. Mode type: transverse • Dataset: wind-triggered Experimental 0.47 Hz Analytical 0.46 Hz Verification Study-Mode Shapes I-

  18. Mode type: vertical • Dataset: wind-storm Experimental 0.68 Hz Analytical 0.62 Hz Verification Study-Mode Shapes II-

  19. Mode type: vertical • Dataset: traffic Experimental 3.47 Hz Analytical 3.15 Hz Verification Study-Mode Shapes III-

  20. Verification Study- Observations - • Experimental Frequencies consistently higher than predicted • Significant variability in the extracted structural dynamic properties

  21. Variability Study • Possible sources of variability: • Environmental Effects (e.g. temperature) • Differences in loading scenarios • Modeling & computational assumptions • Stiffness degradation ↔ deterioration/damage

  22. Variability Study- Method & Scope - • Ten datasets • Ambient operational responses • Similar environmental conditions & loading scenarios • Determination of baseline level of variability • Attributable to numerical accuracy of data and identification process

  23. Variability Study- Data & SSI parameters - • Duration: 900 s • Number of samples: 37500 @ 41.7 Hz • number of response channels: 17

  24. Variability Study- Typical Data -

  25. SSI Stabilization Diagram

  26. Wind Data- Hurricane Juan -

  27. Traffic Data- Summer 2003 -

  28. Variability Study- Results - Modal Assurance Criterion MAC average

  29. Variability Study- Results II - Localized Mode Shape discrepancies

  30. Variability Study- Observations & Implications - • Highly consistent modal frequencies • Positive finding for condition assessment • Uncertainty in damping estimates • High complexity of damping behaviour • Localized mode shape discrepancies • Challenge for mode-shape based damage location • Ongoing research on variability due to environment and loading scenarios

  31. Real-Time Data Processing and Analysis- Motivation & Objective - • Accelerate data processing • Provide timelier analysis results • Facilitate engineering interpretation • Develop continuous condition assessment platform • Achieve more efficient operations and maintenance

  32. Real-Time Data Processing and Analysis- Application Modules- • Processing Module • Input: accelerometer measurements • Pre-processing • Double integration • Output: processed acceleration & displacements • Automatic error correction & data piping

  33. Real-Time Data Processing and Analysis- Application Modules- • Visualization Module • Real-time animation of 3D bridge model • Integrated plotting • Flexible user interaction • Scaling factor • View angle • Playback speeds • Recordings (avi format)

  34. Real-Time Data Processing and Analysis- Application Modules - • Analysis Module • Extensive plotting • Time histories at each stage of processing • Power Spectral Density analysis • System Identification • Empirical Mode Decomposition – Hilbert Spectrum

  35. Structural Health Monitoring of Plaza Bridge David T. Lau Dept of Civil and Environmental EngCarleton University

  36. Data Processing and Management Transducers Data Loggers Field Computer Remote Monitoring

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