IRISE Report: Improving Bridge Assessment

3.4 3D Visualization of Bridge Inspection Results To provide a better visualization of bridge inspection results, we proposed to develop the 3D model of BEAST to assist in the inspection process. In this study, aerial images were collected from BEAST by using a drone mounted with a high resolution HD camera. 3D reconstruction by photogrammetry was used to develop the 3D meshed model of BEAST. Figure 31 shows the developed 3D models of BEAST, and Figure 32 shows the IR condition map overlayed on the 3D model. Details of methodology can be found in Appendix V.

Figure 31. Completed Digital Surface Model of the BEAST Facility

Turn static files into dynamic content formats.

Create a flipbook

Articles inside

15. References

11. Appendix III: Methodology for subsurface defects detection

5.4 Drone-based HD and IR Image Integration

5.3.6 Multi-sensor Data Fusion for NDE

8. Conclusion and Future Work

5.3.4 Ultrasonic Surface Wave (USW

5.3.3 Electrical Resistivity (ER

10. Appendix II: Methodology for multi-class classifier for crack and spall detection

5.6 NDE Data Analysis Summary and Conclusion

5.3.5 Half Cell Potential (HCP

3.4 3D Visualization of Bridge Inspection Results

5. Dissemination, Integration, and Interpretation of BEAST Data

5.2 Development of Performance Measure for A Representative PA Bridge

3.1.4 Discussion and Future Work of Automated Vision-based Inspection

3.1.2 Subsurface Defects Detection

5.3.2 Ground-Penetrating Radar (GPR

5.1 Timing Scale of BEAST Experiment

3.3 Comparison Between Vision Based and NDE Based Inspection Results

Issuu converts static files into: digital portfolios, online yearbooks, online catalogs, digital photo albums and more. Sign up and create your flipbook.