Investigation of Computer Vision Concepts and Methods for Structural Health Monitoring and Identification Applications

This study presents a comprehensive investigation of methods and technologies for developing a computer vision-based framework for Structural Health Monitoring (SHM) and Structural Identification (St-Id) for civil infrastructure systems, with particular emphasis on various types of bridges. SHM is implemented on various structures over the last two decades, yet, there are some issues such as considerable cost, field implementation time and excessive labor needs for the instrumentation of sensors, cable wiring work and possible interruptions during implementation. These issues make it only viable when major investments for SHM are warranted for decision making. For other cases, there needs to be a practical and effective solution, which computer-vision based framework can be a viable alternative. Computer vision based SHM has been explored over the last decade. Unlike most of the vision-based structural identification studies and practices, which focus either on structural input (vehicle location) estimation or on structural output (structural displacement and strain responses) estimation, the proposed framework combines the vision-based structural input and the structural output from non-contact sensors to overcome the limitations given above. First, this study develops a series of computer vision-based displacement measurement methods for structural response (structural output) monitoring which can be applied to different infrastructures such as grandstands, stadiums, towers, footbridges, small/medium span concrete bridges, railway bridges, and long span bridges, and under different loading cases such as human crowd, pedestrians, wind, vehicle, etc. Structural behavior, modal properties, load carrying capacities, structural serviceability and performance are investigated using vision-based methods and validated by comparing with conventional SHM approaches. In this study, some of the most famous landmark structures such as long span bridges are utilized as case studies. This study also investigated the serviceability status of structures by using computer vision-based methods. Subsequently, issues and considerations for computer vision-based measurement in field application are discussed and recommendations are provided for better results. This study also proposes a robust vision-based method for displacement measurement using spatio-temporal context learning and Taylor approximation to overcome the difficulties of vision-based monitoring under adverse environmental factors such as fog and illumination change. In addition, it is shown that the external load distribution on structures (structural input) can be estimated by using visual tracking, and afterward load rating of a bridge can be determined by using the load distribution factors extracted from computer vision-based methods. By combining the structural input and output results, the unit influence line (UIL) of structures are extracted during daily traffic just using cameras from which the external loads can be estimated by using just cameras and extracted UIL. Finally, the condition assessment at global structural level can be achieved using the structural input and output, both obtained from computer vision approaches, would give a normalized response irrespective of the type and/or load configurations of the vehicles or human loads

Computer vision and optimization methods applied to the measurements of in-plane deformations

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The image processing for the target centre detection in digital image

This thesis comprises of five chapters. Chapter one describes basic principles of the digital image, digital image construction and the present status of the digital photogrammetry system, named PHOENICS (PHOtogrammetric ENgineering and Industrial digital Camera System), as developed by H. Rüther (1989). The target's shape analysis in the digital image are presented in chapter two. Chapter three presents the algorithms to detect and locate target on the digital image. These are the least squares adjustment technique, moment method, moment-preserving for edge detection as well as test methods for the evaluation of the various alglorithms. The novel RG method is presented in chapter four. Chapter five introduces the theory of some image processing methods

Displacement filed calculation of large-scale structures using computer vision with physical constrains

Because of the advantages of easy deployment, low cost and non-contact, computer vision-based structural displacement acquisition technique has received wide attention and research in recent years. However, the displacement field acquisition of large-scale structures is a challenging topic due to the contradiction of camera field of view and resolution. This paper presents a large-scale structural displacement field calculation framework with integrated computer vision and physical constraints using only one camera. Firstly, the full-field image of the large-scale structure is obtained by processing the multi-view image using image stitching technique; secondly, the full-field image is meshed and the node displacements are calculated using an improved template matching method; and finally, the non-node displacements are described using shape functions considering physical constraints. The developed framework was validated using a scaled bridge model and evaluated by the proposed evaluation index for displacement field calculation accuracy. This paper can provide an effective way to obtain displacement fields of large-scale structures efficiently and cost-effectively

Improvements in digital image correlation and application in material mechanical test

Digital image correlation (DIC) is a non-contact full-field optical measurement method. With the advantages of high accuracy, low cost, and simple implementation, it has been widely applied in the area of experimental mechanics. In this study, DIC algorithm has been improved in the aspects of the pixel-level searching method and reference frame update strategy. The feature matching based method is proposed to provide an initial guess for all points of interest with semi-subpixel level accuracy in cases with small or large translation, deformation, or rotation. The bisection searching strategy is presented to automatically adjust the frame step for varying practical circumstances. The improved DIC algorithm is implemented and applied to the miniature tensile test. A convenient experimental method to determine the true stress-strain curve is proposed. The instantaneous cross-section area is estimated by only one camera in aid of DIC method. The derived true stress-strain curves and mechanical parameters of metal material Al6061 and CP-Ti from miniature specimens match well with the results of standard specimens, and no dimension dependence has been observed in the results --Abstract, page iv

Positioning System for a Hand-Held Mine Detector

Humanitarian mine clearance aims at reducing the nuisance of regions infected by explosive devices. These devices need to be detected with a high rate of success while keeping a low false alarm rate to reduce time losses and personnel’s fatigue. This chapter describes a positioning system developed to track hand-held detector movements in the context of close-range mine detection. With such a system, the signals captured by the detector over time can be used to build two- or three-dimensional data. The objects possibly present in the data can then be visually appreciated by an operator to detect specific features such as shape or size or known signatures. The positioning system developed in the framework of the HOPE European project requires only a camera and an extra bar. It adds few constraints to current mine clearance procedures and requires limited additional hardware. The software developed for calibration and continuous acquisition of the position is described, and evaluation results are presented

Algorithms for Building High-Accurate Optical Tracking Systems

Die vorliegende Arbeit präsentiert eine Untersuchung von Einflussfaktoren auf die Genauigkeit eines optischen Trackingsystems zur hoch präzisen Koordinatenmessung, wie sie beispielsweise im Bereich der Computer-unterstützten Chirurgie benötigt wird. Zu den Haupteinflussfaktoren gehören die Modellierung der Aufnahmegeometrie, die verwendeten Bildverarbeitungsalgorithmen zur Markensegmentierung, welche sowohl während der Systemkalibrierung als auch während des eigentlichen Messvorgangs verwendet werden, und nicht zuletzt thermische Einflüsse.Wahrend die Modellierung der Kamerageometrie ein gut erforschter Gegenstand sowohl im Bereich der Photogrammetrie als auch des Maschinellen Sehens darstellt, existieren fur den Vergleich von verschiedenen Markentypen und deren Segmentierungsalgorithmen in bezug auf die Messgenauigkeit noch keine umfassenden Ergebnisse. Einen weiteren Bereich, der nahezu nicht untersucht ist, bilden thermische Einflüsse auf die zugrundeliegende Aufnahmegeometrie. Die vorliegende Arbeit legt ihren Schwerpunkt auf diese zwei Bereiche. Zum einen werden verschiedene Algorithmen zur Segmentierung von Messmarken vorgestellt und miteinander verglichen. Den zweiten großen Schwerpunkt bildet eine Analyse von thermischen Einflussen auf Kameras. Es wird ein Verfahren entwickelt, welches den Einfluss von Temperaturänderungen modelliert und so Messfehler kompensieren kann. Die Ergebnisse dieser Arbeit finden Anwendung in der Entwicklung eines optischen Trackingsystems fur den Einsatz in der orthopädischen Chirurgie

A non-contact vision-based system for multi-point displacement monitoring in a cable-stayed footbridge

This is the author accepted manuscript. The final version is available from Wiley via the DOI in this record.Vision-based monitoring receives increased attention for measuring displacements of civil infrastructure such as towers and bridges. Currently, most field applications rely on artificial targets for video processing convenience, leading to high installation effort and focus on only single-point displacement measurement e.g. at mid-span of a bridge. This study proposes a low-cost and non-contact vision-based system for multi-point displacement measurement based on a consumer-grade camera for video acquisition and a custom-developed package for video processing. The system has been validated on a cable-stayed footbridge for deck deformation and cable vibration measurement under pedestrian loading. The analysis results indicate that the system provides valuable information about bridge deformation of the order of a few cm induced, in this application, by pedestrian passing. The measured data enables accurate estimation of modal frequencies of either the bridge deck or the bridge cables and could be used to investigate variations of modal frequencies under varying pedestrian loads

Detection of curved edges at subpixel accuracy using deformable models

One approach to the detection of curves at subpixel accuracy involves the reconstruction of such features from subpixel edge data points. A new technique is presented for reconstructing and segmenting curves with subpixel accuracy using deformable models. A curve is represented as a set of interconnected Hermite splines forming a snake generated from the subpixel edge information that minimizes the global energy functional integral over the set. While previous work on the minimization was mostly based on the Euler-Lagrange transformation, the authors use the finite element method to solve the energy minimization equation. The advantages of this approach over the Euler-Lagrange transformation approach are that the method is straightforward, leads to positive m-diagonal symmetric matrices, and has the ability to cope with irregular geometries such as junctions and corners. The energy functional integral solved using this method can also be used to segment the features by searching for the location of the maxima of the first derivative of the energy over the elementary curve set

Evaluation of collision properties of spheres using high-speed video analysis

Experimental evaluation of the collision properties of spheres is performed using video image analysis techniques. A high-speed Kodak EktaPro1000 video camera is utilized to record a collision sequence between two spheres at 1000 frames/sec, and then the images are analyzed to calculate three dimensional translation and rotation before and after the collision. These quantities are used to compute the collision properties for a pair of one inch nylon spheres, i.e. the coefficient of friction, and the coefficients of normal and tangential restitution. The focus of the thesis is on image analysis techniques that provide high accuracy results even though the image resolution is very low, i.e. 240x192 pixels. The procedure developed here can be extended to smaller size spheres and can also be applicable to other motion analysis expenments involving low resolution images