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A framework for the identification of full-field structural dynamics using sequences of images in the presence of non-ideal operating conditions

Dasari, Sudeep and Dorn, Charles and Yang, Yongchao and Larson, Amy and Mascareñas, David (2018) A framework for the identification of full-field structural dynamics using sequences of images in the presence of non-ideal operating conditions. Journal of Intelligent Material Systems and Structures, 29 (17). pp. 3456-3481. ISSN 1045-389X. https://resolver.caltech.edu/CaltechAUTHORS:20181108-141833191

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Abstract

Recent developments in the ability to automatically and efficiently extract natural frequencies, damping ratios, and full-field mode shapes from video of vibrating structures has great potential for reducing the resources and time required for performing experimental and operational modal analysis at very high spatial resolution. Furthermore, these techniques have the added advantage that they can be implemented remotely and in a non-contact fashion. Emerging full-field imaging techniques therefore have potential to allow the identification of the modal properties of structures in regimes that used to be challenging. For instance, these techniques suggest that the high spatial resolution structural identification could be performed on an aircraft during flight using a ground or aircraft-based imager. They also have the potential to identify the dynamics of microscopic systems. In order to realize this capability it will be necessary to develop techniques that can extract full-field structural dynamics in the presence of non-ideal operating conditions. In this work, we develop a framework for the deployment of emerging algorithms that allow the automatic extraction of high-resolution, full-field modal parameters in the presence of non-ideal operating conditions. One of the most notable non-ideal operating conditions is the rigid body motion of both the structure being measured as well as the imager performing the measurement. We demonstrate an instantiation of the framework by showing how it can be used to address, in-plane, translational, rigid body motion. The development of a frame-to-frame keypoint–based technique for identifying full-field structural dynamics in the presence of either rigid body motion is presented and demonstrated in the context of the framework for the deployment of full-field structural identification techniques in the presence of non-ideal operating conditions. It is expected that this framework will ultimately help enable the collection of full-field structural dynamics using measurement platforms including unmanned aerial vehicles, robotic telescopes, satellites, imagers mounted in high-vibration environments (seismic, industrial, harsh weather), characterization of microscopic structures, and human-carried imagers. If imager-based structural identification techniques mature to the point that they can be used in non-ideal field conditions, it could open up the possibility that the structural health monitoring community will be able to think beyond monitoring individual structures, to full-field structural integrity monitoring at the city scale.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.1177/1045389x17754271DOIArticle
ORCID:
AuthorORCID
Dasari, Sudeep0000-0003-2600-2779
Dorn, Charles0000-0001-6516-2586
Yang, Yongchao0000-0003-1776-3306
Additional Information:© 2018 by SAGE Publications. Article first published online: February 16, 2018; Issue published: October 1, 2018.
Funders:
Funding AgencyGrant Number
Los Alamos National Laboratory20150708PRD2
Subject Keywords:full-field imaging, output-only modal identification, structural dynamics, structural health monitoring, video motion processing
Issue or Number:17
Record Number:CaltechAUTHORS:20181108-141833191
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20181108-141833191
Official Citation:Dasari, S., Dorn, C., Yang, Y., Larson, A., & Mascareñas, D. (2018). A framework for the identification of full-field structural dynamics using sequences of images in the presence of non-ideal operating conditions. Journal of Intelligent Material Systems and Structures, 29(17), 3456–3481. https://doi.org/10.1177/1045389X17754271
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:90765
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:09 Nov 2018 12:58
Last Modified:03 Oct 2019 20:28

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