Dissertation/Thesis Abstract

Structural Health Monitoring and Seismic Response Assessment of Civil Infrastructure Using Target-Tracking Digital Image Correlation
by Ngeljaratan, Luna Nurdianti, Ph.D., University of Nevada, Reno, 2019, 342; 27672110
Abstract (Summary)

The deployment of wireless or non-contact sensing emerges as an innovative monitoring alternative in structural health monitoring (SHM) which facilitates monitoring of remote areas such as under bridges crossing waterways, and most importantly, operates at lower cost due to quicker and cheaper installation of the sensor and data acquisition system. Several previous studies investigated the capabilities and limitations of wireless type sensors. However, there have been issues in data transmission, limited measurement distance, or limited measurement points. To cope with the problems of existing wireless sensor, vision-based measurement systems have been developed and they are currently emerging in the field of SHM. The measurements of vision-based system use images and tracks multiple targets motion between image sequences. Some relevant works concluded that, vision-based using digital image correlation (DIC) technique is viewed as a platform in which mobile computing and wireless-communicating elements converges with the monitoring sensors. Previous work also showed the potential of DIC to lead to an economical and robust system for obtaining direct simultaneous measurements at several locations of realistic infrastructure systems undergoing complex 2D and 3D deformations.

Although major efforts have been dedicated in deploying targettracking DIC inSHM, at least from the academic point of view, robust standard of practice or guidelines for monitoring civil structures and infrastructure systems is not yet available because of

several research gaps that require more research studies. One important gap is associated with the lack of comprehensive studies characterizing displacement measurement accuracy, and more specifically for dynamic response monitoring, of target-tracking DIC since most of the classical work focused more on quantifying the error of strain measurements for stochastic pattern DIC. Moreover, although considerable theoretical work has been done in both image correlation and stereovision, only very few studies considered large-scale 3D experimental validation and verification (V&V) via comparison with mechanical sensors while focused on civil structures. Therefore, one of the major objectives of this dissertation is to fill the identified gap above through dedicated V&V experimental testing with several large-scale applications of dynamic response monitoring under seismic loading. Quantifying displacement measurement errors associated with calibration or DIC post-processing, which was independent from monitoring application or target measurements, was needed.

Target-tracking tracking DIC is a new member in the wireless and non-contact sensor family, and just like the other wireless sensor types, target-tracking DIC faces the possibility of losing data in its raw data signals. If other wireless sensor types may possibly be losing the signal during the transmission, target-tracking DIC data loss is mainly because of overexposure and the motion blur. Another challenge of deploying target tracking DIC in SHM is the trade-off among field of view, sampling rates, recording time and exposure time such that one setting dictates the other settings. Selecting a lower fps rate for monitoring might cause a significant issue when the monitored structure vibratedat high frequencies; higher than half of the adopted fps rate. When higher frequencies of interest need to be captured, cameras with higher fps recording capabilities will be required or otherwise the measurement will be incorrect. Considering these challenges, another major objective of this doctoral work is to explore the feasibility and implement compressive sensing techniques for target-tracking DIC signal reconstruction, signal recovery from data loss, and sampling rate improvement by implementing. To this end, a realistic SHM case study was employed where a pedestrian footbridge at the University of Nevada, Reno campus was monitored as it was excited by pedestrian loading to conduct system identification. The results of system identification of the reconstructed, recovered and improved signals were compared to accelerometers and original DIC along with error estimations.

The last part of the dissertation focused on several large-scale applications of civil infrastructure monitoring using target-tracking DIC. In general, no comprehensive studies have implemented target-tracking DIC for monitoring the dynamic and seismic response of civil structures, e.g. bridges, under extreme events such as earthquakes and used it for post-event condition assessment. Thus, this last part of the study focused on demonstrating the validity of target-tracking DIC measurements in capturing seismic response as well as in identifying structural modal parameters through system identification of several bridge models tested at the Earthquake Engineering Laboratory at UNR. The novelty of this study was in the application as no previous studies used full 3D target-tracking DIC for system identification and monitoring of full structural systems.

Indexing (document details)
Advisor: Moustafa, Mohamed A.
Commitee: Buckle, Ian G., McCallen, David, Pekcan, Gokhan, Yang, Yueran
School: University of Nevada, Reno
Department: Civil and Environmental Engineering
School Location: United States -- Nevada
Source: DAI-B 81/8(E), Dissertation Abstracts International
Subjects: Civil engineering, Engineering
Keywords: Assessment, Digital image correlation, Infrastructure, Seismic, Structural health monitoring, Target tracking
Publication Number: 27672110
ISBN: 9781392706688
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