The work described in this thesis discusses the design of a solar energy harvesting system to support a structural health monitoring system. The objective was to design a photovoltaic system capable of powering a wireless gateway and cellular modem, a static DC 14W load, while meeting certain functional and energy requirements for deployment on a bridge. A literature review of the application, technologies, components, and latest innovations in solar energy technology was completed. A methodology for designing a system for attaching energy harvesting systems onto bridges while meeting design requirements is presented as a tool for engineers and students. The use of the tool was demonstrated through a study which revealed that the methodology aided in producing concepts that were higher in quality, quantity, and better met design requirements. A PV array performance model was used to determine the proper PV module size, battery bank size, panel orientation, the usefulness of a solar tracker and MPPT charge controller, and whether the use of two separate PV modules with independent geometric orientations provide better performance as compared to a single larger panel. It was found from the study that the optimal PV system design specifications were a 120W Polycrystalline PV panel, a 120 A-hr LiFePO4 battery bank, a 45 degree tilt and 0 degrees solar azimuth angle (south), and an MPPT controller. The results from the analytical model also showed that the maximum energy produced with two independent panels would be at a solar azimuth angle of 0 degrees (south) and tilt angles of 45 and 50 degrees respectively. However, these energy gains were insignificant compared to simply increasing the size of the PV module. This result was verified by physical experiments. The physical embodiment of the solar energy harvester with these characteristics, including the mount to the bridge and the panel, was conceptualized, refined, analyzed for structural integrity, and prototyped. / text

Electrical conductivity (or resistivity) of cementitious materials is considered to be a fundamental property and is commonly measured using nondestructive and noninvasive testing techniques. Therefore, electrical measurements are gaining popularity in both research and field applications for structural health monitoring and material characterization of civil engineering infrastructure systems. Based on the results of measurements, the engineer can schedule maintenance more accurately and give an early warning of possible structural failure. Recently, health monitoring systems are capable of significantly increasing the cost efficiency of maintenance and repair by helping engineers improve the safety and maintainability of structures through early damage detection. The research team at the University of Texas at Austin developed a low-cost, passive, wireless conductivity sensor system. Sensors are wirelessly interrogated using external reader during inspection over the service life of the structure to monitor the conductivity variations within concrete. The focus of this work is to assess the condition of cementitious materials by measuring electrical conductivity using passive wireless sensors. By analyzing the measured conductivity data, the condition of the cementitious material, such as extent of hydration, setting and hardening times, and transport phenomena, can be assessed. This document also provides comprehensive information on the design, fabrication, interrogation, and response of conductivity sensor platforms. / text

V této diplomové práci jsou popsané SHM metody používané v letectví a dále jsou udělány MKP simulace šíření ultrazvoukových vln v celokompozitním tenkostěnném materiálu používaném u leteckých konstrukcí. Pro simulaci byla zvolena SHM metoda nazývaná pitch-catch. Simulace byla provedena na dvou různých kompozitových materiálech a každý z nich byl testován třemí různými konfiguracemi s trhlinou a jednou konfigurací bez trhliny. Jako prepocessor byl použit MSC.Patran a jako post processory byli použity MSC.Nastran a MSC.Dytran, jejichž výsledky byli na závěr porovnány. Simulace prokázali, že rychlost šíření a amplituda vln šířících se v simulovaném panelu je trhlinami ovlivněna. Při konfiguracích s trhlinami rychlost šíření i amplituda vln byli menší, než v případě bez trhliny. Jako vhodnější post processor při MKP simulacích se ukázal MSC.Nastran, jehož výsledky byli přesnější a zárověň bylo i snažší správně odečítat hodnoty dat z grafů pro podrobnější pozorování šíření vln.

In den letzten Jahrzehnten ist die Komplexität und Vernetzung einzelner Komponenten im Automobil stetig gewachsen. Der Grund dafür sind immer zahlreicher werdende Systeme im und rund um das Auto, welche das tägliche Leben sicherer und komfortabler machen. Von ABS über elektronische Motorsteuerungen bis hin zu autonom fahrenden Fahrzeugen werden in den nächsten Jahren immer aufwendigere Systeme zum Einsatz kommen. Es wird davon ausgegangen, dass in Zukunft 90% der Innovationen im Fahrzeug von der programmierbaren Elektronik geprägt sein werden, was die Komplexität der Software in einem enormen Maße beeinussen wird. Schon heute wird versucht durch entsprechende Techniken den Entwicklungsaufwand gering zu halten, da der internationale Konkurrenz- und Kostendruck die Industrie dazu zwingt.

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Structural health monitoring (SHM) is a quickly advancing field of study in civil engineering and recent advances in the field are in stark contrast to where the field started. For example modern technology of wireless sensing systems allowed for easier monitoring of structures, but the challenge of limiting the number of instrumented locations has not been overcome with traditional methods. The potential of alternative methods has only been realized in recent years with the increase of model based approaches. In particular, the use of limited measurements to estimate structural response at all locations is appealing. To accomplish this goal, this work approaches SHM by using a numerical model combined with a linear recursive state estimation algorithm, known as the Kalman Filter, to update the model-based prediction with a limited number of real time measurements taken on the structure. A thorough overview of the contents is given here. The first section introduces the topic of SHM and the goal of SHM. Then the challenges and limitation that face SHM are discussed along with the recent advances that can be used to overcome them. In Section 2, the proposed framework, a Kalman filter approach, is established. First, a finite element model is formulated for plate structures using the Mindlin-Reissner plate theory and then this finite element code is verified by a comparison with a commercial FEA software. Then the state space model of the system is defined for use with the Augmented Kalman Filter (AKF); the AKF approach overcomes the intrinsic challenge of unknown excitations for civil structures. The AKF is then formulated and discussed. For Section 3, using the AKF in numerical simulations are conducted for 5 different cases. The first three cases study the advantages of multi-metric measurements, i.e. strain and acceleration measurements combined, versus single metric measurement, i.e. strain measurement only or acceleration measurement only. Following that, the next two cases explore the question of whether multi-metric measurements will always provide the best results. Based on the conclusions from the previous section, Section 4 investigates the application of a genetic algorithm, a search algorithm based of Darwinian principles, to find the optimal sensor placement to use as the input to the AKF. Here the developed search algorithm is used in two cases, the first is to find the optimal placement for the strain measurement only case. Next, the improvements in accuracy that are gained by placing taking more measurements is investigated to determine if the gain in accuracy per added measurement decreases for large numbers of measurements. Section 5 contains the final conclusions about the use of the AKF for SHM of plate structures then the potential opportunities of future work regarding plate structures are discussed.

This thesis presents a development of Structural Health Monitoring (SHM) and Fault Diagnosis based on Artificial Immune System (AIS), a biology-inspired method motivated from the Biological Immune System (BIS). Using the antigen to model structural health or damage condition of specific characteristics and the antibody to represent an information system or a database that can identify the specific damage pattern, the AIS can detect structural damage and then take action to ensure the structural integrity. In this study the antibodies for SHM were first trained and then tested. The feature space in training includes the natural frequencies and the modal shapes extracted from the simulated structural response data including both free-vibration and seismic response data. The concepts were illustrated for a 2-DOF linear mass-spring-damper system and promising results were obtained. It has shown that the methodology can be effectively used to detect, locate, and assess damage if it occurred. Consistently good results were obtained for both feature spaces of the natural frequencies and the modal shapes extracted from both response data sets. As the only exception, some significant errors were observed in the result for the seismic response data when the second modal shape was used as the feature space. The study has shown great promises of the methodology for structural health monitoring, especially in the case when the measurement data are not sufficient. The work lays a solid foundation for future investigations on the AIS application for large-scale complex structures.

An innovative artificial immune system (AIS) is proposed herein for structural health monitoring (SHM) to ensure the structural integrity and functionality. While satisfactory results were obtained by previous AIS schemes, their performance is strongly structural-parameter-value (SPV) dependent and deviations of SPVs in testing from training due to modeling errors and measurement noises significantly deteriorates the AIS' performance. This thesis presents a less SPV-dependent AIS with a three-phase architecture, including damage-existence-detection, damage-location-determination, and damage-severity-estimation, using specially designed feature vectors (FVs) based on structural modal parameters. The maximum-relative-modal-parameter-change is used to detect the damage's existence and estimate its severity, and the pattern in normalized-modal-parameter-change is used to determinate the damage's location. Comparisons between the proposed FVs and their existing counterparts were conducted for 2/3/4-degree-of-freedom structures to illustrate the superior performance and less SPV-dependence of the proposed method, particularly in determining damage location. The proposed AIS was tested on a 4-degree-of-freedom model using 440 randomly generated damage conditions with a different SPV set per condition. A success rate of 95.23% in the determination of damage's existence and its location was obtained. The trained AIS for the 4-degree-of-freedom model was further evaluated by a four-story and two-bay by two-bay prototype structure used in the benchmark problem proposed by the IASC-ASCE Structural Health Monitoring Task Group. Results have shown great potentials of the proposed approach in its real-world applications.

Orientador: Michael John Brennan / Banca: Fabricio Cesar Lobato de Almeida / Banca: Max de Castro Magalhães / Resumo: Este trabalho apresenta o estudo da propagação de ondas em estruturas unidimensionais, como barras e vigas, bem como a metodologia utilizada para a análise de resposta das ondas quando submetidas a descontinuidades estruturais. A motivação deste projeto é o Monitoramento da Integridade Estrutural, SHM, técnica utilizada em engenharia para detectar a presença de falhas em estruturas mecânicas em vários tipos de indústrias como: civis, automobilísticas, aeronáuticas, evitando, assim, problemas futuros e gastos monetários. Existem diversas técnicas para a aplicação de SHM, uma delas utiliza a propagação de ondas. A utilização de ondas é uma ferramenta bastante procurada por empresas atualmente por ser uma técnica não destrutiva e por caracterizar descontinuidades geométricas. Ondas elásticas dispersam sua energia quando encontram uma descontinuidade, portanto, é possível observar o que acontece nesta divisão através dos coeficientes de reflexão e transmissão. Neste contexto, estes coeficientes são modelados e estudados em duas situações: com ondas longitudinais guiadas por barras e com ondas de flexão guiadas por vigas. Neste trabalho, são modelados diferentes tipos de falhas com arranjos de elementos básicos da mecânica: massa, mola e amortecedor. Os dois tipos de ondas submetidas a esses elementos possuem características específicas observadas inclusive no modelamento matemático. Adicionalmente, elaboram-se estruturas com descontinuidade geométrica para aplicação e correlação dos modelos previamente desenvolvidos visando uma relação de frequências de excitação necessárias para qualificação de diferentes formas de descontinuidades localizada para estrutura de material definido / Abstract: This work presents a study on wave propagation in one-dimensional structures, such as rods and beams, and analyses the effects of structural discontinuities on wave motion. The motivation of this project is the Structural Health Monitoring (SHM), technique used in engineering to detect the presence of damage in mechanical structures in several types of industries like: civil, automobile, aeronautical, thus, avoiding future problems and financial costs. There are several techniques for SHM application, and some of them use wave propagation. The use of waves is a tool sought by companies as a non-destructive technique and for being able to characterise geometric discontinuities. Elastic waves scatter their energy when they reach a discontinuity, and this is characterised by the reflection and transmission coefficients of the discontinuity. In this context, these coefficients are studied for two situations: with longitudinal waves guided by rods and with bending waves guided by beams. In this work, two different types of damage are modelled through basic mechanical elements such as mass, spring and damper. Additionally, structures with geometric discontinuity are investigated and compared with the models previously developed in order to gain physical insight into their dynamic behaviour / Mestre

Structural Health Monitoring (SHM) is concerned with the analysis of aerospace, mechanical and civil systems with the objective of identifying damage at its onset. In civil engineering applications, damage may be defined as any change in the structural properties that hinders the current or future performance of that system. This is the premise on which vibration-based techniques are based. Vibration-based methods exploit the response measured directly on the system to solve the SHM assignment. However, also fluctuations in the external conditions may induce changes in the structural properties. For these reasons, the SHM problem is ideally suited to be solved within the context of statistical pattern recognition, which is the discipline concerned with the automatic classification of objects into categories. Within the statistical pattern recognition based SHM framework, the structural response is portrayed by means of a compact representation of its main traits, called damage sensitive features (dsf). In this dissertation, two typologies of dsf are studied: the first type is extracted from the response of the system by means of digital signal processes alone, while the other is obtained by making use of a physical model of the system. In both approaches, the effects of external conditions are accounted for by modeling the damage sensitive features as random variables. While the first method uses outlier analysis tools and delivers a method optimally apt to perform the task of damage detection within the short-term horizon, the second approach, being model-based, allows for a deeper characterization of damage, and it is then more suited for long-term monitoring purposes. In the dissertation, an approach is also proposed that allows the use of the statistical pattern recognition framework when there is limited availability of data to model the damage sensitive features. All proposed methodologies are validated both numerically and experimentally.