Automated 3D Structure Inference of Civil Infrastructure Using a Stereo Camera Set

The commercial far-range (>10m) infrastructure spatial data collection methods are not completely automated. They need significant amount of manual post-processing work and in some cases, the equipment costs are significant. This paper presents a method that is the first step of a stereo videogrammetric framework and holds the promise to address these issues. Under this method, video streams are initially collected from a calibrated set of two video cameras. For each pair of simultaneous video frames, visual feature points are detected and their spatial coordinates are then computed. The result, in the form of a sparse 3D point cloud, is the basis for the next steps in the framework (i.e., camera motion estimation and dense 3D reconstruction). A set of data, collected from an ongoing infrastructure project, is used to show the merits of the method. Comparison with existing tools is also shown, to indicate the performance differences of the proposed method in the level of automation and the accuracy of results.

Automated Detection of Exposed Reinforcement in Post-Earthquake Safety and Structural Evaluations

Post-earthquake structural safety evaluations are currently performed manually by a team of certified inspectors and/or structural engineers. This process is time-consuming and costly, keeping owners and occupants from returning to their businesses and homes. Automating these evaluations would enable faster, and potentially more consistent, relief and response processes. In order to do this, the detection of exposed reinforcing steel is of utmost significance. This paper presents a novel method of detecting exposed reinforcement in concrete columns for the purpose of advancing practices of structural and safety evaluation of buildings after earthquakes. Under this method, the binary image of the reinforcing area is first isolated using a state-of-the-art adaptive thresholding technique. Next, the ribbed regions of the reinforcement are detected by way of binary template matching. Finally, vertical and horizontal profiling are applied to the processed image in order to filter out any superfluous pixels and take into consideration the size of reinforcement bars in relation to that of the structural element within which they reside. The final result is the combined binary image disclosing only the regions containing rebar overlaid on top of the original image. The method is tested on a set of images from the January 2010 earthquake in Haiti. Preliminary test results convey that most exposed reinforcement could be properly detected in images of moderately-to-severely damaged concrete columns.

Comparison of Image-Based and Time-of-Flight-Based Technologies for 3D Reconstruction of Infrastructure

Image-based (i.e., photo/videogrammetry) and time-of-flight-based (i.e., laser scanning) technologies are typically used to collect spatial data of infrastructure. In order to help architecture, engineering, and construction (AEC) industries make cost-effective decisions in selecting between these two technologies with respect to their settings, this paper makes an attempt to measure the accuracy, quality, time efficiency, and cost of applying image-based and time-of-flight-based technologies to conduct as-built 3D reconstruction of infrastructure. In this paper, a novel comparison method is proposed, and preliminary experiments are conducted. The results reveal that if the accuracy and quality level desired for a particular application is not high (i.e., error < 10 cm, and completeness rate > 80%), image-based technologies constitute a good alternative for time-of-flight-based technologies and significantly reduce the time and cost needed for collecting the data on site.

Automated Detection of Exposed Reinforcement in Post-Earthquake Safety and Structural Evaluations

The world is at the threshold of emerging technologies, where new systems in construction, materials, and civil and architectural design are poised to make the world better from a structural and construction perspective. Exciting developments, that are too many to name individually, take place yearly, affecting design considerations and construction practices. This edited book brings together modern methods and advances in structural engineering and construction, fulfilling the mission of ISEC Conferences, which is to enhance communication and understanding between structural and construction engineers for successful design and construction of engineering projects. The articles in this book are those accepted for publication and presentation at the 6th International Structural Engineering and Construction Conference in Zurich. The 6th ISEC Conference in Zurich, Switzerland, follows the overwhelming reception and success of previous ISEC conference in Las Vegas, USA in 2009; Melbourne, Australia in 2007; Shunan, Japan in 2005; Rome, Italy in 2003; and Honolulu, USA in 2001. Many topics are covered in this book, ranging from legal affairs and contracting, to innovations and risk analysis in infrastructure projects, analysis and design of structural systems, materials, architecture, and construction. The articles here are a lasting testimony to the excellent research being undertaken around the world. These articles provide a platform for the exchange of ideas, research efforts and networking in the structural engineering and construction communities. We congratulate and thank the authors for these articles that were selected after intensive peer-review, and our gratitude extends to all reviewers and members of the International Technical Committee. It is their combined contributions that have made this book a reality.

Comparison of Image-Based and Time-of-Flight-Based Technologies for Three-Dimensional Reconstruction of Infrastructure

Image-based (i.e., photo/videogrammetry) and time-of-flight-based (i.e., laser scanning) technologies are typically used to collect spatial data of infrastructure. In order to help architecture, engineering, and construction (AEC) industries make cost-effective decisions in selecting between these two technologies with respect to their settings, this paper makes an attempt to measure the accuracy, quality, time efficiency, and cost of applying image-based and time-of-flight-based technologies to conduct as-built 3D reconstruction of infrastructure. In this paper, a novel comparison method is proposed, and preliminary experiments are conducted. The results reveal that if the accuracy and quality level desired for a particular application is not high (i.e., error < 10 cm, and completeness rate > 80%), image-based technologies constitute a good alternative for time-of-flight-based technologies and significantly reduce the time and cost needed for collecting the data on site.

Comprehensive Property Retrieval and Measurement of Concrete Spalling Using Machine Vision for Post-Earthquake Safety Assessments

Active vibration control (AVC) is a relatively new technology for the mitigation of annoying human-induced vibrations in floors. However, recent technological developments have demonstrated its great potential application in this field. Despite this, when a floor is found to have problematic floor vibrations after construction the unfamiliar technology of AVC is usually avoided in favour of more common techniques, such as Tuned Mass Dampers (TMDs) which have a proven track record of successful application, particularly for footbridges and staircases. This study aims to investigate the advantages and disadvantages that AVC has, when compared with TMDs, for the application of mitigation of pedestrian-induced floor vibrations in offices. Simulations are performed using the results from a finite element model of a typical office layout that has a high vibration response level. The vibration problems on this floor are then alleviated through the use of both AVC and TMDs and the results of each mitigation configuration compared. The results of this study will enable a more informed decision to be made by building owners and structural engineers regarding suitable technologies for reducing floor vibrations.

Rapid entropy-based detection and properties measurement of concrete spalling with machine vision for post-earthquake safety assessments

The current procedures in post-earthquake safety and structural assessment are performed manually by a skilled triage team of structural engineers/certified inspectors. These procedures, and particularly the physical measurement of the damage properties, are time-consuming and qualitative in nature. This paper proposes a novel method that automatically detects spalled regions on the surface of reinforced concrete columns and measures their properties in image data. Spalling has been accepted as an important indicator of significant damage to structural elements during an earthquake. According to this method, the region of spalling is first isolated by way of a local entropy-based thresholding algorithm. Following this, the exposure of longitudinal reinforcement (depth of spalling into the column) and length of spalling along the column are measured using a novel global adaptive thresholding algorithm in conjunction with image processing methods in template matching and morphological operations. The method was tested on a database of damaged RC column images collected after the 2010 Haiti earthquake, and comparison of the results with manual measurements indicate the validity of the method.

Tomographic reconstruction of OH* chemiluminescence in two interacting turbulent flames

The tomographic reconstruction of OH* chemiluminescence was performed on two interacting turbulent premixed bluff-body stabilized flames under steady flow conditions and acoustic excitation. These measurements elucidate the complex three-dimensional (3D) vortex-flame interactions which have previously not been accessible. The experiment was performed using a single camera and intensifier, with multiple views acquired by repositioning the camera, permitting calculation of the mean and phase-averaged volumetric OH* distributions. The reconstructed flame structure and phase-averaged dynamics are compared with OH planar laser-induced fluorescence and flame surface density measurements for the first time. The volumetric data revealed that the large-scale vortex-flame structures formed along the shear layers of each flame collide when the two flames meet, resulting in complex 3D flame structures in between the two flames. With a fairly simple experimental setup, it is shown that the tomographic reconstruction of OH* chemiluminescence in forced flames is a powerful tool that can yield important physical insights into large-scale 3D flame dynamics that are important in combustion instability. © 2013 IOP Publishing Ltd.

Robust network reconstruction in polynomial time

This paper presents an efficient algorithm for robust network reconstruction of Linear Time-Invariant (LTI) systems in the presence of noise, estimation errors and unmodelled nonlinearities. The method here builds on previous work [1] on robust reconstruction to provide a practical implementation with polynomial computational complexity. Following the same experimental protocol, the algorithm obtains a set of structurally-related candidate solutions spanning every level of sparsity. We prove the existence of a magnitude bound on the noise, which if satisfied, guarantees that one of these structures is the correct solution. A problem-specific model-selection procedure then selects a single solution from this set and provides a measure of confidence in that solution. Extensive simulations quantify the expected performance for different levels of noise and show that significantly more noise can be tolerated in comparison to the original method. © 2012 IEEE.

Reconstruction of arbitrary biochemical reaction networks: A compressive sensing approach

Reconstruction of biochemical reaction networks (BRN) and genetic regulatory networks (GRN) in particular is a central topic in systems biology which raises crucial theoretical challenges in system identification. Nonlinear Ordinary Differential Equations (ODEs) that involve polynomial and rational functions are typically used to model biochemical reaction networks. Such nonlinear models make the problem of determining the connectivity of biochemical networks from time-series experimental data quite difficult. In this paper, we present a network reconstruction algorithm that can deal with ODE model descriptions containing polynomial and rational functions. Rather than identifying the parameters of linear or nonlinear ODEs characterised by pre-defined equation structures, our methodology allows us to determine the nonlinear ODEs structure together with their associated parameters. To solve the network reconstruction problem, we cast it as a compressive sensing (CS) problem and use sparse Bayesian learning (SBL) algorithms as a computationally efficient and robust way to obtain its solution. © 2012 IEEE.

Dynamical structure function identifiability conditions enabling signal structure reconstruction

Networks of controlled dynamical systems exhibit a variety of interconnection patterns that could be interpreted as the structure of the system. One such interpretation of system structure is a system's signal structure, characterized as the open-loop causal dependencies among manifest variables and represented by its dynamical structure function. Although this notion of structure is among the weakest available, previous work has shown that if no a priori structural information is known about the system, not even the Boolean structure of the dynamical structure function is identifiable. Consequently, one method previously suggested for obtaining the necessary a priori structural information is to leverage knowledge about target specificity of the controlled inputs. This work extends these results to demonstrate precisely the a priori structural information that is both necessary and sufficient to reconstruct the network from input-output data. This extension is important because it significantly broadens the applicability of the identifiability conditions, enabling the design of network reconstruction experiments that were previously impossible due to practical constraints on the types of actuation mechanisms available to the engineer or scientist. The work is motivated by the proteomics problem of reconstructing the Per-Arnt-Sim Kinase pathway used in the metabolism of sugars. © 2012 IEEE.