Computer vision-based structural assessment exploiting large volumes of images

Visual assessment is a process to understand the state of a structure based on evaluations originating from visual information. Recent advances in computer vision to explore new sensors, sensing platforms and high-performance computing have shed light on the potential for vision-based visual assessment in civil engineering structures. The use of low-cost, high-resolution visual sensors in conjunction with mobile and aerial platforms can overcome spatial and temporal limitations typically associated with other forms of sensing in civil structures. Also, GPU-accelerated and parallel computing offer unprecedented speed and performance, accelerating processing the collected visual data. However, despite the enormous endeavor in past research to implement such technologies, there are still many practical challenges to overcome to successfully apply these techniques in real world situations. A major challenge lies in dealing with a large volume of unordered and complex visual data, collected under uncontrolled circumstance (e.g. lighting, cluttered region, and variations in environmental conditions), while just a tiny fraction of them are useful for conducting actual assessment. Such difficulty induces an undesirable high rate of false-positive and false-negative errors, reducing the trustworthiness and efficiency of their implementation. To overcome the inherent challenges in using such images for visual assessment, high-level computer vision algorithms must be integrated with relevant prior knowledge and guidance, thus aiming to have similar performance with those of humans conducting visual assessment. Moreover, the techniques must be developed and validated in the realistic context of a large volume of real-world images, which is likely contain numerous practical challenges. In this dissertation, the novel use of computer vision algorithms is explored to address two promising applications of vision-based visual assessment in civil engineering: visual inspection, and visual data analysis for post-disaster evaluation. For both applications, powerful techniques are developed here to enable reliable and efficient visual assessment for civil structures and demonstrate them using a large volume of real-world images collected from actual structures. State-of-art computer vision techniques, such as structure-from-motion and convolutional neural network techniques, facilitate these tasks. The core techniques derived from this study are scalable and expandable to many other applications in vision-based visual assessment, and will serve to close the existing gaps between past research efforts and real-world implementations

Degradation of Dissipative Characteristics of Friction Pendulum Isolators due to Thermal Effect

The purpose of the research is to predict the reliability of friction pendulum devices during their service life. These bearings are characterized by the capability to undergo large displacements despite their compact size. This peculiar property makes this device competitive among other commonly used isolation devices such as lead-rubber bearings. In these supports the dissipation of seismic motion occurs exclusively by the friction produced during sliding of the surfaces while the seismic isolation is obtained by the shifting of the natural period of the superstructure. Over the time, the interest of the scientific community for such devices has focused on the study of the friction coefficient involved during the motion and also on its dependence on certain mechanical variables such as velocity and apparent pressure. Several studies have shown that the friction coefficient in a contact problem between polymer (PTFE) and stainless steel deviates from the Coulomb’s friction law. Furthermore, most recent studies have shown that the coefficient of friction is closely related to the increase of temperature due to the thermal effect. This phenomenon consists in a cyclic degradation of the dissipative capacities of friction pendulum that in the design phase is not considered. The observed reduction of energy dissipated during repetitive cycles is often coupled with peak displacements larger than predicted with potential consequences on the whole structure’s safety. This PhD study is composed by 8 chapter and it start with an introduction of the basic concept in seismic base isolation (Chapter 2) while the main characteristics of friction pendulum devices are introduced are defined in Chapter 3. The basic theory of frictional heating useful to describe the increase of temperature which occurs in polymer-stainless steel surface is introduced in chapter 4. Through an experimental campaign carried out with single pendulum bearings, the dependence of the friction coefficient with the temperature rise has been investigated in chapter 5, in order to propose a phenomenological model able to assess the real performance of the friction pendulum. Specifically, in chapter 5 is described the experimental analysis carried out in Caltrans SRMD Testing Facility of San Diego University of California. A series of friction pendulum have been tested at Caltrans SRMD which is equipped with a shaking table test specifically designed for full-scale tests. During the tests, the table was also equipped with a thermographic camera specially calibrated for the type of material tested (polished stainless steel). Thanks to the use of the camera it has been possible to evaluate the temperature rise during the whole testing time and in the portion of the concave surface affected by the thermal heating. In chapter 6, an analytical comparison has been carried out between the friction coefficient recorded during the test and the temperature rise obtained with the analytical model of degradation of the friction coefficient introduced in chapter 4. Finally in chapter 7 a prediction model that takes into account mechanical variables such as velocity and apparent pressure, and also the degradation of dissipative characteristics of a friction pendulum due to thermal effects, is given. The proposed friction model is suitable for immediate implementation in generalized structural analysis codes and provides an important design tool for a more realistic assessment of the seismic response of structures equipped with Friction Pendulum devices

Automatic vehicle detection and tracking in aerial video

This thesis is concerned with the challenging tasks of automatic and real-time vehicle detection and tracking from aerial video. The aim of this thesis is to build an automatic system that can accurately localise any vehicles that appear in aerial video frames and track the target vehicles with trackers. Vehicle detection and tracking have many applications and this has been an active area of research during recent years; however, it is still a challenge to deal with certain realistic environments. This thesis develops vehicle detection and tracking algorithms which enhance the robustness of detection and tracking beyond the existing approaches. The basis of the vehicle detection system proposed in this thesis has different object categorisation approaches, with colour and texture features in both point and area template forms. The thesis also proposes a novel Self-Learning Tracking and Detection approach, which is an extension to the existing Tracking Learning Detection (TLD) algorithm. There are a number of challenges in vehicle detection and tracking. The most difficult challenge of detection is distinguishing and clustering the target vehicle from the background objects and noises. Under certain conditions, the images captured from Unmanned Aerial Vehicles (UAVs) are also blurred; for example, turbulence may make the vehicle shake during flight. This thesis tackles these challenges by applying integrated multiple feature descriptors for real-time processing. In this thesis, three vehicle detection approaches are proposed: the HSV-GLCM feature approach, the ISM-SIFT feature approach and the FAST-HoG approach. The general vehicle detection approaches used have highly flexible implicit shape representations. They are based on training samples in both positive and negative sets and use updated classifiers to distinguish the targets. It has been found that the detection results attained by using HSV-GLCM texture features can be affected by blurring problems; the proposed detection algorithms can further segment the edges of the vehicles from the background. Using the point descriptor feature can solve the blurring problem, however, the large amount of information contained in point descriptors can lead to processing times that are too long for real-time applications. So the FAST-HoG approach combining the point feature and the shape feature is proposed. This new approach is able to speed up the process that attains the real-time performance. Finally, a detection approach using HoG with the FAST feature is also proposed. The HoG approach is widely used in object recognition, as it has a strong ability to represent the shape vector of the object. However, the original HoG feature is sensitive to the orientation of the target; this method improves the algorithm by inserting the direction vectors of the targets. For the tracking process, a novel tracking approach was proposed, an extension of the TLD algorithm, in order to track multiple targets. The extended approach upgrades the original system, which can only track a single target, which must be selected before the detection and tracking process. The greatest challenge to vehicle tracking is long-term tracking. The target object can change its appearance during the process and illumination and scale changes can also occur. The original TLD feature assumed that tracking can make errors during the tracking process, and the accumulation of these errors could cause tracking failure, so the original TLD proposed using a learning approach in between the tracking and the detection by adding a pair of inspectors (positive and negative) to constantly estimate errors. This thesis extends the TLD approach with a new detection method in order to achieve multiple-target tracking. A Forward and Backward Tracking approach has been proposed to eliminate tracking errors and other problems such as occlusion. The main purpose of the proposed tracking system is to learn the features of the targets during tracking and re-train the detection classifier for further processes. This thesis puts particular emphasis on vehicle detection and tracking in different extreme scenarios such as crowed highway vehicle detection, blurred images and changes in the appearance of the targets. Compared with currently existing detection and tracking approaches, the proposed approaches demonstrate a robust increase in accuracy in each scenario

Innovative Methods and Materials in Structural Health Monitoring of Civil Infrastructures

In the past, when elements in sructures were composed of perishable materials, such as wood, the maintenance of houses, bridges, etc., was considered of vital importance for their safe use and to preserve their efficiency. With the advent of materials such as reinforced concrete and steel, given their relatively long useful life, periodic and constant maintenance has often been considered a secondary concern. When it was realized that even for structures fabricated with these materials that the useful life has an end and that it was being approached, planning maintenance became an important and non-negligible aspect. Thus, the concept of structural health monitoring (SHM) was introduced, designed, and implemented as a multidisciplinary method. Computational mechanics, static and dynamic analysis of structures, electronics, sensors, and, recently, the Internet of Things (IoT) and artificial intelligence (AI) are required, but it is also important to consider new materials, especially those with intrinsic self-diagnosis characteristics, and to use measurement and survey methods typical of modern geomatics, such as satellite surveys and highly sophisticated laser tools

Rock-shape and its role in rockfall dynamics

Rockfall threaten infrastructure and people throughout the world. Estimating the runout dynamics of rockfall is commonly performed using models, providing fundamental data for hazard management and mitigation design. Modelling rockfall is made challenging by the complexity of rock-ground impacts. Much research has focused on empirical impact laws that bundle the rock-ground impact into a single parameter, but this approach fails to capture characteristics associated with the impact configuration and, in particular, the effects of rock-shape. While it is apparent that particular geological settings produce characteristic rock-shapes, and that different rock-shapes may produce characteristic runout dynamics, these aspects of rockfall are poorly understood. This study has focused on investigating the mechanics behind the notion that different rock-shapes produce characteristic runout dynamics and trajectories. The study combines field data on rockfall runout, trajectory and dynamics, laboratory analogue testing in controlled conditions, and numerical modelling of the influence of rock-shape. Initially rock-shape, deposition patterns and rockfall dynamics were documented at rockfall sites in Switzerland and New Zealand. This informed a detailed study of individual rock-ground impacts on planar slopes in which laboratory-scale and numerical rockfall experiments were combined to isolate the role of rock-shape on runout. Innovatively, the physical experiments captured the dynamics of impacts and runout paths using high speed video tracking and a sensor bundle with accelerometers and gyroscopes. Numerical experiments were performed using a 3-D rigid-body rockfall model that considers rock-shape, and has allowed the variability of rockfall behaviour to be explored beyond the limitations of physical experimentation. The main findings of the study were on understanding rockfall-ground impacts, the influence of rock-shape on rockfall dynamics, and influence of rock sphericity. By measuring velocity, rotational speed, impact and runout character, it has been possible to quantify the variability of individual rock-ground impacts as a function of rock-shape. Investigation of single rebounds reveals that if classical restitution coefficients are applied, $R_n$ values greater than unity are common and rebounds are highly variable regardless of constant contact parameters. It is shown that this variability is rooted in the inherent differences in the magnitudes of the principal moment of inertia of a rock body brought about by rock-shape. Any departure from a perfect sphere induces increased range and variability in rock-ground rebound characteristics. In addition to the popular description of a rock bouncing down slope, rebounds involve the pinning of an exterior edge point on the rock, creating a moment arm which effectively levers the rock into ballistic trajectory as it rotates. Observations reveal that the angle of the impact configuration plays a key role in the resulting rebound, whereby low angles produce highly arched rebounds, while large impact angles produce low flat rebounds. The type of rebound produced has a strong bearing on the mobility of the rocks and their ability to maintain motion over a long runout. The mobility of rocks is also shown to be related to rotation, which is governed by the differences in the principal inertial axes as a function of rock-shape. Angular velocity measurements about each principal inertial axis indicate that rocks have a tendency to seek rotation about the axis of largest inertia, as the most stable state. Rotations about intermediate and small axes of inertia and transitions between rotational axes are shown to be unstable and responsible for the dispersive nature of runout trajectories, which are inherent characteristics of different rock-shapes. The findings of this research demonstrate the importance of rock-shape in rockfall runout dynamics and illustrate how it is essential that the rock-shape is included in rockfall modelling approaches if the variability of rockfall behaviour is to be simulated

Experimental Study of Rocking Motion of Rigid Bodies on Deformable Medium via Monocular Videogrammetry

The study of rigid body rocking is applicable to a wide variety of structural and non-structural elements. The current applications range from bridge pier and shallow footing design to hospital and industrial equipment, even art preservation. Despite the increasing number of theoretical and simulation studies of rocking motion, few experimental studies exist. Of those that have been published, most are focused on a constrained version of the complete problem introducing modifications to the physical problem with the purpose of eliminating either sliding, uplift or the three dimensional response of the body. However, all of these phenomena may affect the response of an unrestrained rocking body. Furthermore, the majority of the experimental studies that have been published have used methods that are ill-suited to comprehensive three dimensional experimental analysis of the problem. The intent of this work is two-fold. First, to present a computer vision method that allows for the experimental measurement of the rigid body translation and rotation time histories in three dimensions. Experimental results obtained with this method will be presented to demonstrate that it obtains greater than 97% accuracy when compared against National Institute of Standards and Technology traceable displacement sensors. The experimental results highlight important phenomena predicted in some state-of-the-art models for 3D rocking behavior. Second, to present experimental evidence of the importance of characterizing the support medium as deformable instead of the commonly assumed rigid model. It will be shown in this work that this assumption of a rigid support may in some cases lead to non-conservative analysis that is unable to predict rocking motion and, in some cases, even failure

Internationales Kolloquium über Anwendungen der Informatik und Mathematik in Architektur und Bauwesen : 20. bis 22.7. 2015, Bauhaus-Universität Weimar

The 20th International Conference on the Applications of Computer Science and Mathematics in Architecture and Civil Engineering will be held at the Bauhaus University Weimar from 20th till 22nd July 2015. Architects, computer scientists, mathematicians, and engineers from all over the world will meet in Weimar for an interdisciplinary exchange of experiences, to report on their results in research, development and practice and to discuss. The conference covers a broad range of research areas: numerical analysis, function theoretic methods, partial differential equations, continuum mechanics, engineering applications, coupled problems, computer sciences, and related topics. Several plenary lectures in aforementioned areas will take place during the conference. We invite architects, engineers, designers, computer scientists, mathematicians, planners, project managers, and software developers from business, science and research to participate in the conference

Review article: The use of remotely piloted aircraft systems (RPASs) for natural hazards monitoring and management

The number of scientific studies that consider possible applications of remotely piloted aircraft systems (RPASs) for the management of natural hazards effects and the identification of occurred damages strongly increased in the last decade. Nowadays, in the scientific community, the use of these systems is not a novelty, but a deeper analysis of the literature shows a lack of codified complex methodologies that can be used not only for scientific experiments but also for normal codified emergency operations. RPASs can acquire on-demand ultra-high-resolution images that can be used for the identification of active processes such as landslides or volcanic activities but can also define the effects of earthquakes, wildfires and floods. In this paper, we present a review of published literature that describes experimental methodologies developed for the study and monitoring of natural hazard

Training of Crisis Mappers and Map Production from Multi-sensor Data: Vernazza Case Study (Cinque Terre National Park, Italy)

This aim of paper is to presents the development of a multidisciplinary project carried out by the cooperation between Politecnico di Torino and ITHACA (Information Technology for Humanitarian Assistance, Cooperation and Action). The goal of the project was the training in geospatial data acquiring and processing for students attending Architecture and Engineering Courses, in order to start up a team of "volunteer mappers". Indeed, the project is aimed to document the environmental and built heritage subject to disaster; the purpose is to improve the capabilities of the actors involved in the activities connected in geospatial data collection, integration and sharing. The proposed area for testing the training activities is the Cinque Terre National Park, registered in the World Heritage List since 1997. The area was affected by flood on the 25th of October 2011. According to other international experiences, the group is expected to be active after emergencies in order to upgrade maps, using data acquired by typical geomatic methods and techniques such as terrestrial and aerial Lidar, close-range and aerial photogrammetry, topographic and GNSS instruments etc.; or by non conventional systems and instruments such us UAV, mobile mapping etc. The ultimate goal is to implement a WebGIS platform to share all the data collected with local authorities and the Civil Protectio

Comparison study of precise monitoring techniques applied to engineering specimens tested under dynamic loading

Initially, the thesis shows a state of the art for structural health monitoring techniques and procedures. Different types of instrumentations and sensors employed under different requirements, which are presented with the view to monitor a variety of structural issues resulted by numerous conditions. It also presents examples from the literature following the proposed monitoring strategy as a novel pattern. These show how close-range digital photogrammetry and strain gauges have been employed in the past with the view to obtain strain evaluation assessments of the relevant monitored structural elements. Based on three surveys which have been carried out in a historical masonry church in Athens (Greece), the methodology of the thesis is generated with the experimental framework being also formed. Eight experiments have been carried out, five of them at the Advanced Structures Laboratory (CEGE – UCL), one at the Concrete Laboratory (CEGE – UCL) and two of them at the Earthquake and Large Structures Laboratory (EQUALS – University of Bristol). Two scale engineering specimens are employed for the experimental needs, both are scaled down using as a prototype element, the north-eastern wall of the studied church. The five experiments which are carried out in CEGE, are made on small scale masonry specimens, of 1/17th scale and the two experiments in EQUALS are made on large scale masonry specimens, of 1/5th scale. All the seven experiments are dynamically loaded. The only static loaded experiment is carried out at the Concrete Laboratory and it is made on a masonry specimen. Through the comparison of the two monitoring methods, close-range digital photogrammetry (CRDP) and strain gauges (SG), is concluded that both methods can capture a change in strain, on the tested specimens, when a crack is occurring