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Abstract

Measuring the dynamic displacements of a structure provides a comprehensive understanding of the structure, especially when subjected to different types of dynamic loading (i.e., wind, traffic, impact loads, blast loads). Despite their usefulness, direct displacement measurements are typically not collected due to the cumbersome logistical issues of sensor placement and maintenance and the impracticality of instrumenting contact-based sensors across all significant structures. In this context, this study proposes a novel dual stereo vision technique to measure the dynamic displacement of structures using a portable, non-contact measurement system that involves an uncrewed aerial system (UAS) and four optical cameras. One pair of cameras tracks the three-component (x, y, and z) motion of a region of interest (ROI) on a structure with respect to the UAS system; the other pair of cameras measures the six degrees of freedom motion (6-DOF) (both rotational and translational motion) of the UAS system by tracking a stationary reference. The motion of the UAS is then compensated for to recover the true dynamic displacement of the ROI. The proposed dual stereo vision technique realizes simultaneous measurement of all three components of the structure’s displacements and 6-DOF of UAS motion through a mathematically elegant process. The unique dual stereo vision technique allows flexibility in choosing a global reference coordinate system, greatly enhancing the feasibility of applying the new technology in various field environments. This new technique has overcome the major challenge of significant UAS motions in full-scale applications. Furthermore, this technique relies on natural features and eliminates the requirement of artificial targets on the structure, permitting applications to difficult-to-access structures.

How to Cite

Perry, Brandon J., Yanlin Guo, and Rebecca Atadero. Noncontact Dynamic Three-Component Displacement Measurement with a Dual Stereovision-Enabled Uncrewed Aerial System, MPC-24-553. North Dakota State University - Upper Great Plains Transportation Institute, Fargo: Mountain-Plains Consortium, 2024.