<div>This dissertation broadly focuses on autonomous condition assessment of civil infrastructures using vision-based methods, which present a plausible alternative to existing manual techniques. A region-based convolutional neural network (Faster R-CNN) is exploited for the detection of various earthquake-induced damages in reinforced concrete buildings. Four different damage categories are considered such as surface crack, spalling, spalling with exposed rebars, and severely buckled rebars. The performance of the model is evaluated on image data collected from buildings damaged under several past earthquakes taking place in different parts of the world. The proposed algorithm can be integrated with inspection drones or mobile robotic platforms for quick assessment of damaged buildings leading to expeditious planning of retrofit operations, minimization of damage cost, and timely restoration of essential services. </div><div><br></div><div> </div><div> Besides, a computer vision-based approach is presented to track the evolution of a damage over time by analysing historical visual inspection data. Once a defect is detected in a recent inspection data set, its spatial correspondences in the data collected during previous rounds of inspection are identified leveraging popular computer vision-based techniques. A single reconstructed view is then generated for each inspection round by synthesizing the candidate corresponding images. The chronology of damage thus established facilitates time-based quantification and lucid visual interpretation. This study is likely to enhance the efficiency structural inspection by introducing the time dimension into the autonomous condition assessment pipeline.</div><div><br></div><div> </div><div> Additionally, this dissertation incorporates depth fusion into a CNN-based semantic segmentation model. A 3D animation and visual effect software is exploited to generate a synthetic database of spatially aligned RGB and depth image pairs representing various damage categories which are commonly observed in reinforced concrete buildings. A number of encoding techniques are explored for representing the depth data. Besides, various schemes for fusion of RGB and depth data are investigated to identify the best fusion strategy. It was observed that depth fusion enhances the performance of deep learning-based damage segmentation algorithms significantly. Furthermore, strategies are proposed to manufacture depth information from corresponding RGB frame, which eliminates the need of depth sensing at the time of deployment without compromising on segmentation performance. Overall, the scientific research presented in this dissertation will be a stepping stone towards realizing a fully autonomous structural condition assessment pipeline.</div>

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Das Exzellenzcluster MERGE in Chemnitz entwickelte ein Fertigungsverfahren, welches ein Werkstoff herstellt. Dieser Werkstoff ist vielseitig einsetzbar. So kann er z.B. in einem Automobil als ein modernes Steuerungselement dienen. Ein zentraler Bestandteil dieses Werkstoffes ist eine Schicht aus Piezokristallen. Aus diesen Kristallen besteht ebenfalls ein Piezosensor. Da der Piezosensor im Bereich des Structural Health Monitorings (SHM) oft verwendet wird, soll der Werkstoff auf seine Einsetzbarkeit als Sensor im diesen Bereich überprüft werden. Das SHM beschreibt die periodische Begutachtung des Bauteils auf das Vorhandensein eines Schadens. Bestimmt wird der Schaden indem Signaleigenschaften des vom Sensor aufgenommenen Signals untersucht werden. Anhand der Veränderung dieser Signaleigenschaften kann der Zustand des Bauteils bestimmt werden. In dieser Arbeit wird eine rechteckige Metallplatte aus Aluminium als Bauteil untersucht. Dieses Bauteil wurde zur Verstärkung der Steifigkeit mit einer Schicht aus Glasfasern beklebt. Angeregt und Beschädigt wird das Bauteil durch eine Prüfmaschine. Die Beschädigung des Bauteils erfolgt durch die Erhöhung der Intensität der Kraft. Als Signaleigenschaften werden in der Arbeit die Kurzzeitenergie und die Intensität der Frequenzanteile des aufgenommenen Signals vom Werkstoff untersucht.

Dans le domaine de la construction, la détection automatisée et à distance de l’endommagementdes structures en béton est d’une importance capitale. En effet, lescontraintes économiques actuelles imposent une réduction des coûts de maintenancetandis que les impératifs en termes de sécurité et de qualité sont de plus en plus stricts.Dans le cadre de cette thèse, des transducteurs piézoélectriques intégrés sont utilisésafin de suivre en temps réel le comportement du béton. Ces transducteurs sont faitsde PZT, une céramique piézoélectrique particulièrement adaptée au suivi à l’aide d’ultrasonsde par ses faibles dimensions, son faible coût et la large bande de fréquenced’utilisation. Un système de monitoring ultrasonore à faible voltage et ultra rapide a étéentièrement conçu dans le cadre de cette thèse. Le système est basé sur des mesuresultrasonores bilatérales entre un émetteur et un récepteur. Le système d’acquisitiondes données développé permet d’atteindre jusqu’à 150 mesures par seconde et decalculer en temps réel un indice d’endommagement sur base des mesures effectuées.L’indice d’endommagement est basé sur la première partie de l’onde transmise (ondedirecte) plutôt que sur l’onde tardive. Le système a démontré qu’il est capable de détecterl’apparition de fissures dans le béton avant qu’elles ne soient visuellement apparenteset qu’il permet de suivre de suivre l’initiation de l’endommagement jusqu’à la rupturepour des mécanismes de fissuration très rapides, voire fragiles. Le fait d’intégrer lestransducteurs à l’intérieur de la structure permet potentiellement d’améliorer l’efficacitédes transducteurs ultrasonores à condition que les couches d’enrobage de l’élémentpiézoélectrique soient adéquatement choisis. Une partie importante du travail réaliséa été consacrée au développement d’une méthode innovante et fiable pour concevoirde nouveaux designs de transducteurs optimisés à la fois dans du béton frais ou durci.Nous avons choisi de tirer avantage du mode radial de vibration de disques piézoélectriquepeu coûteux au mode de vibration selon l’épaisseur. Ce dernier requiert en effetdes éléments plus épais ou des matériaux piézoélectriques composites plus coûteuxet dès lors peu appropriés à être intégré définitivement dans une structure en béton.Nous démontrons par ailleurs que les matériaux piézoélectriques composites à base dematériaux cimentaires qui sont abondamment étudiés semblent en réalité peu adaptés àêtre utilisés comme transducteurs ultrasonores, contrairement à des composites plusclassiques. Une attention particulière a été portée à comparer le fonctionnement destransducteurs externes et intégrés. Nous montrons par exemple que si les performancesdes transducteurs externes peuvent être améliorées sur base de la théorie d’adaptationde l’impédance acoustique, il en va tout autrement pour les transducteurs intégrés / Doctorat en Sciences de l'ingénieur et technologie / info:eu-repo/semantics/nonPublished

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This research effort explored the possibility of using interwoven conductive and nonconductive fibers in a composite laminate for structural health monitoring (SHM). Traditional SHM systems utilize fiber optics, piezoelectrics, or detect defects by nondestructive test methods by use of sonar graphs or x-rays. However, these approaches are often expensive, time consuming and complicated. The primary objective of this research was to apply a resistance based method of structural health monitoring to a composite structure to determine structural integrity and presence of defects. The conductive properties of fiber such as carbon, copper, or constantan - a copper-nickel alloy - can be utilized as sensors within the structure. This allows the structure to provide feedback via electrical signals to a user which are essential for evaluating the health of the structure. In this research, the conductive fiber was made from constantan wire which was embedded within a composite laminate; whereas prepreg fiberglass, a nonconductive material, serves as the main structural element of the laminate. A composite laminate was constructed from four layers of TenCate 7781 “E” fiberglass and BT250E-1 resin prepreg. Integrating the constantan within the composite laminate provides a sensory element which supplies measurements of structural behavior. Thus, with fiberglass, epoxy, and a constantan conductive element, a three-part composite laminate is developed. Test specimens used in this research were fabricated using a composite air press with the recommended manufacturer cure cycle. A TenCate BT250E-1 Resin System and 7781 "E" impregnated glass-fiber/epoxy weave was used. A constantan wire of 0.01” gauge diameter was integrated into the composite structure. The composite laminate specimen with the integrated SHM system was tested under tensile and flexural loads employing test standards specified by ASTM D3039 and D7264, respectively. These test methods were modified to determine the behavior of the laminate in the elastic range only. A tension and flexural delamination test case was also developed to investigate the sensitivity of the SHM system to inherent defects. Moreover, material characteristic tests were completed to validate manufacturer provided material characteristics. The specimens were tested while varying the constantan configurations, such as the sensor length and orientation. A variety of techniques to integrate the sensor were also investigated. Two different measurement methods were used to determine strain. Strain measurements were made with Instron Bluehill 2 software and correlated to strain obtained by the structural health monitoring system with the use of a data acquisition code written to interact with a micro-ohm-meter. The experimental results showed good agreement between measurements made by the two different methods of measurement. Observations discovered that varying the length of the sensor element improved sensitivity, but resulted in different prediction models when compared to cases with less sensor length. The predictions are based on the gauge factor, which was determined for the each test case. This value provides the essential relationship between resistance and strain. Experiments proved that the measured gauge factor depended greatly on the sensor length and orientation. The correlation was of sufficient accuracy to predict strain values in a composite laminate without the use of any added tools or equipment besides the ohm-meter. Analytical solutions to the loading cases were developed to validate results obtained during experiments. The solutions were in good agreement with the experimental results.

One of the key areas that have attracted attention in the construction industry today is Structural Health Monitoring, more commonly known as SHM. It is a concept developed to monitor the quality and longevity of various engineering structures. The incorporation of such a system would help to continuously track health of the structure, indicate the occurrence/presence of any damage in real time and give us an idea of the number of useful years for the same. Being a recently conceived idea, the state of the art technique in the field is straight forward - populating a given structure with sensors and extracting information from them. In this regard, instrumenting with too many sensors may be inefficient as this could lead to superfluous data that is expensive to capture and process. This research aims to explore an alternate SHM technique that optimizes the data acquisition process by eliminating the amount of redundant data that is sensed and uses this sufficient data to detect and locate the fault present in the structure. Efficient data acquisition requires a mechanism that senses just the necessary amount of data for detection and location of fault. For this reason Compressive Sensing (CS) is explored as a plausible idea. CS claims that signals can be reconstructed from what was previously believed to be incomplete information by Shannon's theorem, taking only a small amount of random and linear non - adaptive measurements. As responses of many physical systems contain a finite basis, CS exploits this feature and determines the sparse solution instead of the traditional least - squares type solution.As a first step, CS is demonstrated by successfully recovering the frequency components of a simple sinusoid. Next, the question of how CS compares with the conventional Fourier transform is analyzed. For this, recovery of temporal frequencies and signal reconstruction is performed using the same number of samples for both the approaches and the errors are compared. On the other hand, the FT error is gradually minimized to match that of CS by increasing the number of regularly placed samples. Once the advantages are established, feasibility of using CS to detect damage in a single degree of freedom system is tested under unforced and forced conditions. In the former scenario, damage is indicated when there is a change in natural frequency of vibration of the system after an impact. In the latter, the system is excited harmonically and damage is detected by a change in amplitude of the system's vibration. As systems in real world applications are predominantly multi-DOF, CS is tested on a 2-DOF system excited with a harmonic forcing. Here again, damage detection is achieved by observing the change in the amplitude of vibration of the system. In order to employ CS for detecting either a change in frequency or amplitude of vibration of a structure subjected to realistic forcing conditions, it would be prudent to explore the reconstruction of a signal which contains multiple frequencies. This is accomplished using CS on a chirp signal. Damage detection is clearly a spatio-temporal problem. Hence it is important to additionally explore the extension of CS to spatial reconstruction. For this reason, mode shape reconstruction of a beam with standard boundary conditions is performed and validated with standard/analytical results from literature. As the final step, the operation deflection shapes (ODS) are reconstructed for a simply supported beam using CS to establish that it is indeed a plausible approach for a less expensive SHM. While experimenting with the idea of spatio-temporal domain, the mode shape as well as the ODS of the given beam are examined under two conditions - undamaged and damaged. Damage in the beam is simulated as a decrease in the stiffness coefficient over a certain number of elements. Although the range of modes to be examined heavily depends on the structure in question, literature suggests that for most practical applications, lower modes are more dominant in indicating damage. For ODS on the other hand, damage is indicated by observing the shift in the recovered spatial frequencies and it is confirmed by the reconstructed response.

Structural Health Monitoring is a useful tool for reducing maintenance costs and improving the life and performance of engineering structures. Impedance-Based SHM utilizes the coupled electromechanical behavior of piezoelectric materials to detect adverse changes and material and mechanical failures of structures. Environmental variables such as temperature present a challenge to assessing the veracity of damage detected through statistical modeling of impedance signals. An effective frequency shift method was developed to compensate impedance measurements for changes resulting from environmental temperature fluctuations. This thesis investigates how the accuracy of this method can be improved and be applied to a 100oF range of temperatures. Building up the idea of eliminating temperature effects from impedance measurements, this thesis investigates the possibility of using statistical moments to create a temperature independent impedance baseline. / Master of Science

Structural Health Monitoring (SHM) of automobile tires has been an active area of research in the last few years. Within this area, the monitoring of strain on tires using wireless devices and networks is gaining prominence because these techniques do not require any wired connections. Various tire manufacturers are looking into SHM of automobile tires due to the Transportation Recall Enhancement, Accountability and Documentation (TREAD) act which demands installation of tire pressure monitoring devices within the tire. Besides measuring tire pressures, tire manufactures are also examining ways to measure strain and temperature as well to enhance overall safety of an automobile. A sensor system that can measure the overall strain of a tire is known as a centralized strain sensing system. However, a centralized strain sensing system cannot find the location and severity of the damage on the tire, which is a basic requirement. Various sensors such as acceleration and optical sensors have also been proposed to be used together to get more local damage information on the tire. In this thesis we have developed a strain sensing system that performs local strain measurements on the tire and transmits them to a console inside the vehicle wirelessly. Our sensing system utilizes a new sensing material called Metal RubberTM which is shown to be conductive like metal, and flexible as rubber. Also, we have also developed a reliable and an energy efficient geographic routing protocol for transporting strain data wirelessly from a tire surface to the driver of the automobile. / Master of Science

Civil infrastructure throughout the world serves as main arteries for commerce and transportation, commonly forming the backbone of many societies. Bridges have been and remain a crucial part of the success of these civil networks. However, the crucial elements have been built over centuries and have been subject to generations of use. Many current bridges have outlived their intended service life or have been retrofitted to carry additional loads over their original design. A large number of these historic bridges are still in everyday use and their condition needs to be monitored for public safety. Transportation infrastructure authorities have implemented various inspection and management programs throughout the world, mainly visual inspections. However, careful visual inspections can provide valuable information but it has limitations in that it provides no actual stress-strain information to determine structural soundness. Structural Health Monitoring (SHM) has been a growing area of research as officials need to asses and triage the aging infrastructure with methods that provide measurable response information to determine the health of the structure. A rapid improvement in technology has allowed researchers to start using new sensors and algorithms to understand the structural parameters of tested structures due to known and unknown loading scenarios. One of the most promising methods involves the use of wireless sensor nodes to measure structural responses to loads in real time. The structural responses can be processed to help understand the modal parameters, determine the health of the structure, and potentially identify damage. For example, modal parameters of structures are typically used when designing the lateral system of a structure. A better understanding of these parameters can lead to better and more efficient designs. Usually engineers rely on a finite element analysis to identify these parameters. By observing the actual parameters displayed during field testing, the theoretical FE models can be validated for accuracy. This paper will present the field testing of a historic wrought iron truss bridge, in a case study, to establish a repeatable procedure to be used as reference for the testing of other similar structures.