A Novel Approach for 3D-Structural Identification through Video Recording: Magnified Tracking†
AbstractAdvancements in optical imaging devices and computer vision algorithms allow the exploration of novel diagnostic techniques for use within engineering systems. A recent field of application lies in the adoption of such devices for non-contact vibrational response recordings of structures, allowing high spatial density measurements without the burden of heavy cabling associated with conventional technologies. This, however, is not a straightforward task due to the typically low-amplitude displacement response of structures under ambient operational conditions. A novel framework, namely Magnified Tracking (MT), is proposed herein to overcome this limitation through the synergistic use of two computer vision techniques. The recently proposed phase-based motion magnification (PBMM) framework, for amplifying motion in a video within a defined frequency band, is coupled with motion tracking by means of particle tracking velocimetry (PTV). An experimental campaign was conducted to validate a proof-of-concept, where the dynamic response of a shear frame was measured both by conventional sensors as well as a video camera setup, and cross-compared to prove the feasibility of the proposed non-contact approach. The methodology was explored both in 2D and 3D configurations, with PTV revealing a powerful tool for the measurement of perceptible motion. When MT is utilized for tracking “imperceptible” structural responses (i.e., below PTV sensitivity), via the use of PBMM around the resonant frequencies of the structure, the amplified motion reveals the operational deflection shapes, which are otherwise intractable. The modal results extracted from the magnified videos, using PTV, demonstrate MT to be a viable non-contact alternative for 3D modal identification with the benefit of a spatially dense measurement grid. View Full-Text
- Supplementary File 1:
ZIP-Document (ZIP, 9926 KB)
Share & Cite This Article
Harmanci, Y.E.; Gülan, U.; Holzner, M.; Chatzi, E. A Novel Approach for 3D-Structural Identification through Video Recording: Magnified Tracking. Sensors 2019, 19, 1229.
Harmanci YE, Gülan U, Holzner M, Chatzi E. A Novel Approach for 3D-Structural Identification through Video Recording: Magnified Tracking. Sensors. 2019; 19(5):1229.Chicago/Turabian Style
Harmanci, Yunus E.; Gülan, Utku; Holzner, Markus; Chatzi, Eleni. 2019. "A Novel Approach for 3D-Structural Identification through Video Recording: Magnified Tracking." Sensors 19, no. 5: 1229.
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.