A novel applications of photogrammetry for retaining wall assessment

Retaining walls are critical geotechnical assets and their performance needs to be monitored in accordance to transportation asset management principles. Current practices for retaining wall monitoring consist mostly of qualitative approaches that provide limited engineering information or the methods include traditional geodetic surveying, which may provide high accuracy and reliability, but is costly and time-consuming. This study focuses on evaluating failure modes of a 2.43 m × 2.43 m retaining wall model using three-dimensional (3D) photogrammetry as a cost-effective quantitative alternative for retaining wall monitoring. As a remote sensing technique, photogrammetry integrates images collected from a camera and creates a 3D model from the measured data points commonly referred to as a point cloud. The results from this photogrammetric approach were compared to ground control points surveyed with a total station. The analysis indicates that the accuracy of the displacement measurements between the traditional total station survey and photogrammetry were within 1–3 cm. The results are encouraging for the adoption of photogrammetry as a cost-effective monitoring tool for the observation of spatial changes and failure modes for retaining wall condition assessment

Evaluation of photogrammetry and inclusion of control points: Significance for infrastructure monitoring

Structure from Motion (SfM)/Photogrammetry is a powerful mapping tool in extracting three-dimensional (3D) models from photographs. This method has been applied to a range of applications, including monitoring of infrastructure systems. This technique could potentially become a substitute, or at least a complement, for costlier approaches such as laser scanning for infrastructure monitoring. This study expands on previous investigations, which utilize photogrammetry point cloud data to measure failure mode behavior of a retaining wall model, emphasizing further robust spatial testing. In this study, a comparison of two commonly used photogrammetry software packages was implemented to assess the computing performance of the method and the significance of control points in this approach. The impact of control point selection, as part of the photogrammetric modeling processes, was also evaluated. Comparisons between the two software tools reveal similar performances in capturing quantitative changes of a retaining wall structure. Results also demonstrate that increasing the number of control points above a certain number does not, necessarily, increase 3D modeling accuracies, but, in some cases, their spatial distribution can be more critical. Furthermore, errors in model reproducibility, when compared with total station measurements, were found to be spatially correlated with the arrangement of control points

Advanced Photogrammetry-Based Techniques for Condition Assessment of Infrastructure Systems and Structural Components

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

A Novel Application of Photogrammetry for Retaining Wall Assessment

Retaining walls are critical geotechnical assets and their performance needs to be monitored in accordance to transportation asset management principles. Current practices for retaining wall monitoring consist mostly of qualitative approaches that provide limited engineering information or the methods include traditional geodetic surveying, which may provide high accuracy and reliability, but is costly and time-consuming. This study focuses on evaluating failure modes of a 2.43 m × 2.43 m retaining wall model using three-dimensional (3D) photogrammetry as a cost-effective quantitative alternative for retaining wall monitoring. As a remote sensing technique, photogrammetry integrates images collected from a camera and creates a 3D model from the measured data points commonly referred to as a point cloud. The results from this photogrammetric approach were compared to ground control points surveyed with a total station. The analysis indicates that the accuracy of the displacement measurements between the traditional total station survey and photogrammetry were within 1–3 cm. The results are encouraging for the adoption of photogrammetry as a cost-effective monitoring tool for the observation of spatial changes and failure modes for retaining wall condition assessment

Digital Image Correlation Advances in Structural Evaluation Applications: A Review

Structural evaluations are important for monitoring performance and behavior changes that occur due to environmental or other loading conditions. As a renowned experimental mechanics technique, digital image correlation (DIC) has become a widely accepted tool for obtaining not only qualitative, but quantitative structural engineering measurements. In this review, the principles of DIC for displacement field measurements are presented through structural evaluation illustrations. Several developing studies of the method in combination with other techniques for novel assessment approaches are also discussed. The method has grown immensely from conception, and its significance for paving the way to infrastructure resiliency framework is further highlighted. Ongoing DIC measurement challenges can also be reviewed in addition to leading initiatives for addressing future needs in evaluating the structural infrastructure. Overall, this review promotes the flexibility of DIC for implementation as a fully deployable structural evaluation method with great sustainable implications

Evaluation of Photogrammetry and Inclusion of Control Points: Significance for Infrastructure Monitoring

Structure from Motion (SfM)/Photogrammetry is a powerful mapping tool in extracting three-dimensional (3D) models from photographs. This method has been applied to a range of applications, including monitoring of infrastructure systems. This technique could potentially become a substitute, or at least a complement, for costlier approaches such as laser scanning for infrastructure monitoring. This study expands on previous investigations, which utilize photogrammetry point cloud data to measure failure mode behavior of a retaining wall model, emphasizing further robust spatial testing. In this study, a comparison of two commonly used photogrammetry software packages was implemented to assess the computing performance of the method and the significance of control points in this approach. The impact of control point selection, as part of the photogrammetric modeling processes, was also evaluated. Comparisons between the two software tools reveal similar performances in capturing quantitative changes of a retaining wall structure. Results also demonstrate that increasing the number of control points above a certain number does not, necessarily, increase 3D modeling accuracies, but, in some cases, their spatial distribution can be more critical. Furthermore, errors in model reproducibility, when compared with total station measurements, were found to be spatially correlated with the arrangement of control points

A Novel Application of Photogrammetry for Retaining Wall Assessment

Retaining walls are critical geotechnical assets and their performance needs to be monitored in accordance to transportation asset management principles. Current practices for retaining wall monitoring consist mostly of qualitative approaches that provide limited engineering information or the methods include traditional geodetic surveying, which may provide high accuracy and reliability, but is costly and time-consuming. This study focuses on evaluating failure modes of a 2.43 m × 2.43 m retaining wall model using three-dimensional (3D) photogrammetry as a cost-effective quantitative alternative for retaining wall monitoring. As a remote sensing technique, photogrammetry integrates images collected from a camera and creates a 3D model from the measured data points commonly referred to as a point cloud. The results from this photogrammetric approach were compared to ground control points surveyed with a total station. The analysis indicates that the accuracy of the displacement measurements between the traditional total station survey and photogrammetry were within 1–3 cm. The results are encouraging for the adoption of photogrammetry as a cost-effective monitoring tool for the observation of spatial changes and failure modes for retaining wall condition assessment

Final reports: Mechanics of complex materials, Summer 2004

The Mechanics of Complex Materials is a ten-week undergraduate research program hosted by the Department of Theoretical and Applied Mechanics at the University of Illinois at Urbana-Champaign. The dual purposes of this program are (1) to introduce undergraduate students from a broad background to modern problems in the mechanics of materials and (2) to encourage the students to attend graduate school and pursue a career in research. Support for the program is provided by the National Science Foundation and the Department of Defense, through the Research Experience for Undergraduates. [More ...]published or submitted for publicationis not peer reviewe

Evaluation of commercially available remote sensors for highway bridge condition assessment

Improving transportation infrastructure inspection methods and the ability to assess conditions of bridges has become a priority in recent years as the transportation infrastructure continues to age. Current bridge inspection techniques consist largely of labor-intensive subjective measures for quantifying deterioration of various bridge elements. Some advanced nondestructive testing techniques, such as ground- penetrating radar, are being implemented; however, little attention has been given to remote sensing technologies. Remote sensing technologies can be used to assess and monitor the condition of bridge infrastructure and improve the efficiency of inspection, repair, and rehabilitation efforts. Most important, monitoring the condition of a bridge using remote sensors can eliminate the need for traffic disruption or total lane closure because remote sensors do not come in direct contact with the structure. The purpose of this paper is to evaluate 12 potential remote sensing technologies for assessing the bridge deck and superstructure condition. Each technology was rated for accuracy, commercial availability, cost of measurement, precollection preparation, complexity of analysis and interpretation, ease of data collection, stand-off distance, and traffic disruption. Results from this study demonstrate the capabilities of each technology and their ability to address bridge challenges