Dongming Feng - Computer Vision for Structural Dynamics and Health Monitoring

Chapter6explores a method for simultaneous identification of structural parameters and unknown excitation forces by using only displacement response (i.e. output‐only), as in reality it is often highly difficult to measure excitation forces (i.e. input). Numerical analysis investigates the accuracy, convergence, and robustness of the identified results. Laboratory experiments on a beam structure accurately identified the hammer excitation forces as well as the beam stiffness from the beam displacement response measured by a single camera, validating this output‐only method and demonstrating its potential for low‐cost, long‐term SHM.

Chapter 7 presents the application of the computer vision sensor for cost‐effective estimation of tension forces in cables, the most important component in cable‐supported bridges and roof structures. Compared with the existing vibration method based on acceleration measurements, which requires the installation of sensors on the cable, noncontact computer vision measurement of the cable vibration represents significant time and cost savings. This computer vision–based method is implemented in two engineering projects to estimate the cable forces of the cable‐supported roof structure of the Hard Rock Stadium in Florida and the suspender forces of the Bronx‐Whitestone Bridge in New York. Satisfactory agreement is found between cable forces measured by the vision‐based sensor and conventional accelerometers.

Chapter 8 provides an overview of the achievements made thus far in computer vision sensor technology through a state‐of‐the‐art literature review as well as a summary of this book. It also discusses challenges and opportunities, which the authors hope will inspire continued research on an extended adoption of computer vision technology for solving civil and structural engineering problems.

Appendix Afurther introduces the fundamentals of digital image processing using MATLAB, including digital image representation, noise removal, edge detection, and discrete Fourier transform.

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