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Date of Award
2017
Document Type
Campus Access Dissertation
Degree Name
Doctor of Philosophy in Civil Engineering (PhD)
Administrative Home Department
Department of Civil and Environmental Engineering
Advisor 1
Qingli Dai
Advisor 2
Thomas Oommen
Committee Member 1
Zhanping You
Committee Member 2
Rudiger Escobar Wolf
Abstract
There is a great demand to deploy innovative structural health monitoring techniques to detail the condition or performance of infrastructure systems and/or components. Innovative techniques are desired to efficiently assess the condition of infrastructure and provide inspectors with detailed information on the structures performance. In condition assessment procedures, some of the safety issues for inspectors are the systematic changes in the structure’s shape or dimensions known as the deformation and displacement structures endure. Common methods to monitor infrastructure require hands-on instrumentation, great labor, time and resources. Deploying remote sensing technologies provides a hands-off efficient way to analyze the current states of infrastructure systems. Optical remote sensing or digital technologies are sought to enable quick data collection of the material or component of interest and evaluate changes over time. Digital imaging processing using photogrammetry principles have been shown to be comparable evaluation tools for determining alterations and quantifying changes on systems.
Photogrammetry is the science of extracting three-dimensional (3D) information from two-dimensional (2D) photographs. Photogrammetry based Digital Image Correlation (DIC) is a method in which digital images of the specimen’s surface before and after loading are compared, and details about the structure’s planar deformation can be determined. Photogrammetry presents great potential for a monitoring tool for infrastructure systems, but expanding its application for geotechnical assets such a retaining walls would further validate its applicability for measuring unique failure behavior. Furthermore, comparative measurements with photogrammetry techniques further advances its capability to measure accurate changes on infrastructure systems or models. This dissertation will illustrate the application of photogrammetric-based techniques
for assessing performance of infrastructure systems and evaluating structural components. Results from laboratory testing and field demonstrations validate great comparability of the photogrammetry techniques for characterizing changes and performance of materials when compared with traditional and numerical modeling techniques. Measurement errors obtained in this study were as small as a few millimeters and within 1 pixel scales. Thus, a cost-effective, time-efficient, comparably accurate and convenient method for deformation measurement of infrastructure systems is achieved. This research advocates for the integration of photogrammetry techniques as a condition assessment tool for infrastructure systems and beyond.
Recommended Citation
Oats, Renee, "Advanced Photogrammetry-Based Techniques for Condition Assessment of Infrastructure Systems and Structural Components", Campus Access Dissertation, Michigan Technological University, 2017.