Dissertations / Theses on the topic 'Damage identification and location'
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Bandara, Arachchillage Rupika Priyadarshani. "Damage identification and condition assessment of building structures using frequency response functions and neural networks." Thesis, Queensland University of Technology, 2013. https://eprints.qut.edu.au/61196/4/Rupika_Bandara_Thesis.pdf.
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This thesis investigated the viability of using Frequency Response Functions in combination with Artificial Neural Network technique in damage assessment of building structures. The proposed approach can help overcome some of limitations associated with previously developed vibration based methods and assist in delivering more accurate and robust damage identification results. Excellent results are obtained for damage identification of the case studies proving that the proposed approach has been developed successfully.
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Kelly, Brendan T. "A Newly Proposed Method for Detection, Location, and Identification of Damage in Prestressed Adjacent Box Beam Bridges." Ohio University / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1339520527.
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Tappert, Peter M. "Damage identification using inductive learning." Thesis, This resource online, 1994. http://scholar.lib.vt.edu/theses/available/etd-05092009-040651/.
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Al-Tamimi, Adnan N. J. "Damage location in structures by monitoring vibration characteristics." Thesis, Aston University, 1985. http://publications.aston.ac.uk/11848/.
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The aim of this work was to investigate the feasibility of detecting and locating damage in large frame structures where visual inspection would be difficult or impossible. This method is based on a vibration technique for non-destructively assessing the integrity of structures by using measurements of changes in the natural frequencies. Such measurements can be made at a single point in the structure. The method requires that initially a comprehensive theoretical vibration analysis of the structure is undertaken and from it predictions are made of changes in dynamic characteristics that will occur if each member of the structure is damaged in turn. The natural frequencies of the undamaged structure are measured, and then routinely remeasured at intervals . If a change in the natural frequencies is detected a statistical method. is used to make the best match between the measured changes in frequency and the family of theoretical predictions. This predicts the most likely damage site. The theoretical analysis was based on the finite element method. Many structures were extensively studied and a computer model was used to simulate the effect of the extent and location of the damage on natural frequencies. Only one such analysis is required for each structure to be investigated. The experimental study was conducted on small structures In the laboratory. Frequency changes were found from inertance measurements on various plane and space frames. The computational requirements of the location analysis are small and a desk-top micro computer was used. Results of this work showed that the method was successful in detecting and locating damage in the test structures.
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Yamamoto, Kyosuke. "Bridge Damage Identification Using Vehicle Response." 京都大学 (Kyoto University), 2012. http://hdl.handle.net/2433/159406.
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Liu, Xuefeng. "Vibration-based structural damage identification techniques." Thesis, University of Bristol, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.445826.
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Xing, Shutao. "Structural Identification and Damage Identification using Output-Only Vibration Measurements." DigitalCommons@USU, 2011. https://digitalcommons.usu.edu/etd/1067.
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This dissertation studied the structural identification and damage detection of civil engineering structures. Several issues regarding structural health monitoring were addressed.
The data-driven subspace identification algorithm was investigated for modal identification of bridges using output-only data. This algorithm was tested through a numerical truss bridge with abrupt damage as well as a real concrete highway bridge with actual measurements. Stabilization diagrams were used to analyze the identified results and determine the modal characteristics. The identification results showed that this identification method is quite effective and accurate.
The influence of temperature fluctuation on the frequencies of a highway concrete bridge was investigated using ambient vibration data over a one-year period of a highway bridge under health monitoring. The data were fitted by nonlinear and linear regression models, which were then analyzed.
The substructure identification by using an adaptive Kalman filter was investigated by applying numerical studies of a shear building, a frame structure, and a truss structure. The stiffness and damping were identified successfully from limited acceleration responses, while the abrupt damages were identified as well. Wavelet analysis was also proposed for damage detection of substructures, and was shown to be able to approximately locate such damages.
Delamination detection of concrete slabs by modal identification from the output-only data was proposed and carried out through numerical studies and experimental modal testing. It was concluded that the changes in modal characteristics can indicate the presence and severity of delamination. Finite element models of concrete decks with different delamination sizes and locations were established and proven to be reasonable.
Pounding identification can provide useful early warning information regarding the potential damage of structures. This thesis proposed to use wavelet scalograms of dynamic response to identify the occurrence of pounding. Its applications in a numerical example as well as shaking table tests of a bridge showed that the scalograms can detect the occurrence of pounding very well.
These studies are very useful for vibration-based structural health monitoring.
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Moaveni, Babak. "System and damage identification of civil structures." Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 2007. http://wwwlib.umi.com/cr/ucsd/fullcit?p3284170.
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Thesis (Ph. D.)--University of California, San Diego, 2007.Title from first page of PDF file (viewed January 14, 2008). Available via ProQuest Digital Dissertations. Vita. Includes bibliographical references.
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Wang, Dexin. "Structural damage identification in the frequency domain." Diss., The University of Arizona, 1999. http://hdl.handle.net/10150/284350.
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This study presents novel approaches for direct damage identification of structures in the frequency domain. Relations between structural stiffness variations and measured system responses are formulated, thus opening the possibility of locating structural damage in terms of the reduction in the local stiffness when analytical baseline models are not available. After this, the related identifiability is discussed under the noise-free condition. In identifying damage in structural points, generic joint elements with only translational degrees of freedom are defined to parameterize the stiffness variations in the joints. Since ill-conditioning is a common problem in system identification and damage detection, a solution regularization based on parameter subset selection is proposed and used with least squares methods. A substructure-based parameter-recursive algorithm is developed for selecting parameter subsets to make use of the fact that the damage is local in structures. The proposed methods are verified by various simulated examples in which systematic modeling errors are present. Finally, the methods are also applied to the degradation identification of a vehicle structure.
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El-Gamal, Mohamed A. "Fault location and parameter identification in analog circuits." Ohio : Ohio University, 1990. http://www.ohiolink.edu/etd/view.cgi?ohiou1172776742.
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Maouche, Mohamed. "Protection against re-identification attacks in location privacy." Thesis, Lyon, 2019. http://www.theses.fr/2019LYSEI089.
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De nos jours, avec la large propagation de différents appareils mobiles, de nombreux capteurs accompagnent des utilisateurs. Ces capteurs peuvent servir à collecter des données de mobilité qui sont utiles pour des urbanistes ou des chercheurs. Cependant, l'exploitation de ces données soulèvent de nombreuses menaces quant à la préservation de la vie privée des utilisateurs. En effet, des informations sensibles tel que le lieu domicile, le lieu de travail ou même les croyances religieuses peuvent être inférées de ces données. Durant la dernière décennie, des mécanismes de protections appelées "Location Privacy Protection Mechanisms (LPPM)" ont été proposé. Ils imposent des guarenties sur les données (e.g., k-anonymity ou differential privacy), obfusquent les informations sensibles (e.g., efface les points d'intéret) ou sont une contre-mesure à des attaques particulières. Nous portons notre attention à la ré-identification qui est un risque précis lié à la préservation de la vie privée dans les données de mobilité. Il consiste en a un attaquant qui des lors qu'il reçoit une trace de mobilité anonymisée, il cherche à retrouver l'identifiant de son propriétaire en la rattachant à un passif de traces non-anonymisées des utilisateurs du système. Dans ce cadre, nous proposons tout d'abords des attaques de ré-identification AP-Attack et ILL-Attack servant à mettre en exergue les vulnérabilités des mécanismes de protections de l'état de l'art et de quantifier leur efficacité. Nous proposons aussi un nouveau mécanisme de protection HMC qui utilise des heat maps afin de guider la transformation du comportement d'un individu pour qu'il ne ressemble plus au soi du passée mais à un autre utilisateur, le préservant ainsi de la ré-identification. Cet modification de la trace de mobilité est contrainte par des mesures d'utilité des données afin de minimiser la qualité de service ou les conclusions que l'on peut tirer à l'aide de ces donnéesWith the wide propagation of handheld devices, more and more mobile sensors are being used by end users on a daily basis. Those sensors could be leveraged to gather useful mobility data for city planners, business analysts and researches. However, gathering and exploiting mobility data raises many privacy threats. Sensitive information such as one’s home or workplace, hobbies, religious beliefs, political or sexual preferences can be inferred from the gathered data. In the last decade, Location Privacy Protection Mechanisms (LPPMs) have been proposed to protect user data privacy. They alter data mobility to enforce formal guarantees (e.g., k-anonymity or differential privacy), hide sensitive information (e.g., erase points of interests) or act as countermeasures for particular attacks. In this thesis, we focus on the threat of re-identification which aims at re-linking an anonymous mobility trace to the know past mobility of its user. First, we propose re-identification attacks (AP-Attack and ILL-Attack) that find vulnerabilities and stress current state-of-the-art LPPMs to quantify their effectiveness. We also propose a new protection mechanism HMC that uses heat maps to guide the transformation of mobility data to change the behaviour of a user, in order to make her look similar to someone else rather than her past self which preserves her from re-identification attacks. This alteration of mobility trace is constrained with the control of the utility of the data to minimize the distortion in the quality of the analysis realized on this data
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Liu, Ming. "Multidimensional damage state identification using phase space warping /." View online ; access limited to URI, 2005. http://0-wwwlib.umi.com.helin.uri.edu/dissertations/dlnow/3188065.
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Ho, Yuen Kim. "Structural damage identification with changes in vibration characteristics." Thesis, Imperial College London, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.251910.
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Chen, Hua-Peng. "Structural damage identification from measured vibration modal data." Thesis, University of Glasgow, 1998. http://theses.gla.ac.uk/3478/.
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A novel non-linear perturbation theory based on the characteristic equations for structural dynamic systems is developed, which can provide an exact relationship between the perturbation of structural parameters and the perturbation of modal parameters. Then, depending on information about different types of the measured vibration modal data available, a system of governing equations based on the developed theory is derived, which can be utilised for general applications, such as eigendata modification, model updating, and damage identification, suitable for all types of structures, including framed structures and continua. A number of computational procedures based on the derived non-linear governing equations are presented for structural damage identification, which can be suitable for various cases of the measured vibration modal data available, such as only natural frequencies, complete mode shapes, locally complete mode shapes, and incomplete mode shapes. The effectiveness and convergence performance for the proposed approaches are demonstrated by various numerical examples, and the sensitivities of many factors to inverse predictions of structural damage are also investigated. The results for different types of structures, either framed structures or continua, indicate that the proposed approaches can be successful in not only predicting the location of damage but also in determining the extent of structural damage, while at the same time information about only a limited amount of the measured modal data is required. Furthermore, it is found that the proposed approaches are capable of providing information on the exact expanded damaged mode shapes, even if a very limited DOF's readings are available. Structural modelling problems, which have to be considered in structural analysis and damage identification, are discussed. It is shown that structural damage can be identified correctly from the proposed approaches using information about different types of the measured modal data, regardless of different structural models considered and different types of elements used. Therefore, a suitable structural model can be selected in order to properly identify structural damage depending on the available information about modal data
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Torres, Reynier Hernández. "Vibration-based damage identification using hybrid optimization algorithms." Instituto Nacional de Pesquisas Espaciais (INPE), 2017. http://urlib.net/sid.inpe.br/mtc-m21b/2017/08.18.16.12.
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The inverse problem of structural damage identification is addressed in this thesis. The inverse solution is obtained by solving an optimization problem using different hybrid algorithms. The forward structural model is solved by Finite Element codes. FORTRAN code developed by the research group of the Laboratório Associado de Computação e Matemática Aplicada (LAC) of the Instituto Nacional de Pesquisas Espaciais (INPE) was applied to some problems, and for other numerical experiments the NASTRAN software was employed. The acceleration, velocity or displacement time history could be used as experimental data in this methodology. The objective function is formulated as the sum of the squared difference between the measured displacement and the data calculated by the forward model. Different hybrid metaheuristics are tested, using a two-step approach. The first step performs the exploration, and the second one carries out the exploitation, starting from the best solution found in the first step. One optimization approach combines the Multi-Particle Collision Algorithm (MPCA) with the Hooke-Jeeves (HJ) direct search method. MPCA is improved using different mechanisms derived from the Opposition-Based Learning, such as Center-Based Sampling and Rotation-Based Learning. Other applied optimizer is the novel q-gradient, and it is also hybridized with HJ method. The methodology is tested on structures with different complexities. Time-invariant damage was assumed to generate the synthetic measurements. Noiseless and noisy data were considered in tests using models implemented in FORTRAN. Most of the experiments were performed using a full set of data, from all possible nodes, and an experiment was done using a reduced dataset with a low level of noise in data. Noiseless data were considered with experiments using NASTRAN. In this case, the experiments were performed using a full set of data. In general, good estimations for damage location and severity are achieved. Some false positives have appeared, but damages were well identified.O problema inverso da identificação de danos estruturais é abordado nesta tese. A solução inversa é obtida resolvendo um problema de otimização usando diferentes algoritmos híbridos. O modelo direto estrutural é resolvido pelo Método dos Elementos Finitos. Código FORTRAN desenvolvido pelo grupo de pesquisa do Laboratório Associado de Computação e Matemática Aplicada (LAC) do Instituto Nacional de Pesquisas Espaciais (INPE) foi aplicado em alguns problemas e, para outros experimentos numéricos, o software NASTRAN foi empregado. O histórico de tempo de aceleração, velocidade ou deslocamento pode ser usado como dados experimentais nesta metodologia. A função objetivo é formulada como a soma da diferença quadrática entre o deslocamento medido e os dados calculados pelo modelo direto. Diferentes metaheurísticas híbridas são testadas, usando uma abordagem em duas etapas. A primeira etapa realiza a exploração em todo o espaço de busca, e a segunda etapa realiza a intensificação a partir da melhor solução encontrada pela primeira etapa. Uma abordagem de otimização combina o Algoritmo de Colisão de Múltiplas Partículas (MPCA) com o método de busca direta Hooke-Jeeves (HJ). O MPCA é melhorado usando diferentes mecanismos derivados da Aprendizagem Baseada na Oposição, como são a Amostragem Baseada no Centro, e a Aprendizagem Baseada em Rotação. Outro otimizador aplicado é o novo q-gradiente, que também é hibridado com o método HJ. A metodologia é testada em estruturas com diferentes complexidades. Supõe-se que os danos são invariante no tempo para gerar as medidas experimentais sintéticas. Dados sem ruído e com diferentes níveis de ruído foram considerados em testes usando modelos implementados em FORTRAN. A maioria dos experimentos foi realizada usando um conjunto completo de dados, de todos os nós possíveis, e um dos experimentos foi feito usando um conjunto incompleto de dados, com um baixo nível de ruído. Para os experimentos utilizando o NASTRAN, foram considerados dados sintéticos sem ruído, e foi utilizado o conjunto completo de dados. Em geral, boas estimativas para localização e gravidade do dano foram alcançadas. Alguns falsos positivos apareceram nas estimativas, mas os danos presentes nos sistemas foram bem identificados.
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Liu, Chang. "Drive-By Bridge Damage Identification Through Virtual Simulations." Thesis, North Dakota State University, 2019. https://hdl.handle.net/10365/31624.
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With massive infrastructures built in US, timely condition assessment of these infrastructures becomes critical to daily traffic and economics. Due to high cost, long time consumption of direct condition assessment methods, such as closing traffic for sensor installation and monitoring, indirect bridge monitoring has become a promising method. However, the technology is in its initial stage and needs substantial refinement. In this research, virtual simulation approaches, both in 2D and 3D, are used to model the bridge and vehicle interaction through ABAQUS. Artificial Damages were embedded to the model according to different locations and different levels of intensities. With the modelled outcomes, the hypothesis of identifying damages through the responses of the vehicle will be tested. From the simulated vehicle responses, bridge frequencies and damage locations and sizes could be identified accurately through short time flourier transformation and mode shape difference.
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Madden, Ryan J. "Development of Robust Control Techniques towards Damage Identification." Cleveland State University / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=csu1460986638.
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Murugesan, Kaviraj. "Damage detection on railway bridges using system identification." Thesis, Karlstads universitet, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-28595.
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Lertpaitoonpan, Wirat. "Bridge damage detection using a system identification method." [Florida] : State University System of Florida, 2000. http://etd.fcla.edu/etd/uf/2000/amt2446/WiratDissertation3-10-00.pdf.
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Thesis (Ph. D.)--University of Florida, 2000.Title from first page of PDF file. Document formatted into pages; contains xvi, 155 p.; also contains graphics. Vita. Includes bibliographical references (p. 152-154).
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Vo, Peter Hoa. "Experimental study of the time domain damage identification." Diss., The University of Arizona, 2003. http://hdl.handle.net/10150/280457.
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A theoretical and experimental study was undertaken to validate the use of a novel time-domain system identification (SI) method for detecting changes in stiffnesses of uniform cross section fixed-fixed and simply supported beams. By quantifying the reduction of beam's elemental stiffnesses, the location of damage can be detected. The Iterative Least Squares (ILS-UI) algorithm, a novel, time-domain SI algorithm, being developed at the University of Arizona for nondestructive evaluation of structures, is used for this purpose. The ILS-UI algorithm requires the use of nodal response time histories to develop an equivalent multi-degree-of-freedom model in which the number of node points is equal to the number of sensors used in the experiment. To optimize the number of sensors, a finite element model was developed in which the beam was discretized into an optimum number of node points, such that nodal responses at these node points are equivalent to that of the continuous beam. As a prelude to the experimental validation, a simulation was performed to study errors in the numerical integration of a digitized signal for three different rules: trapezoidal, Simpson's and Boole's. It was shown that Simpson's rule and Boole's rule yield smaller errors than the trapezoidal rule, especially when lower sampling rates are used. Several post processing techniques to remove noise, to filter out high frequencies and remove slope and offset from a data set were also demonstrated. In the first phase of the validation experiments, the optimum number of node points was determined for the fixed beam. Also, a method was developed to scale angular response based on the measured transverse response. The ILS-UI algorithm was then used to predict element stiffnesses for the fixed beam. The stiffness predictions did not converge. This prompted an investigation to determine the root cause of the failure. It was found that amplitude and phase errors in the accelerometer's measurements were the root cause of the failure. After this was determined, an alternative approach was developed to mitigate the amplitude and phase shift errors. To validate the alternative approach, nodal responses were measured for the beam with and without damage. The ILS-UI algorithm was demonstrated to successfully quantify reduction in the beam's element stiffnesses and the location of damage was identified.
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Zhang, Qing. "Location and identification of unexploded ordnance using borehole magnetometry." Thesis, University of Liverpool, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.433782.
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Crumlin, Alex Justin. "Methods for short-circuit identification and location in automobiles." Thesis, Massachusetts Institute of Technology, 2006. http://hdl.handle.net/1721.1/36777.
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Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006."June 2006."
Includes bibliographical references (leaf 133).
As the number of electrical components in cars increases at a rapid rate, so too does the chance for electrical failure. A method for locating shorts to the chassis of a car is developed in this thesis. The developed technique is capable of detecting the approximate location of current being injected into the body of the car using several sensors placed strategically throughout the car. This technique can then be used in the manufacturing process and in the field where it can notify the operator of any short-circuit related problems in their car.
by Alex Justin Crumlin.
M.Eng.
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Ge, Ma. "Structural damage detection and identification using system dynamic parameters." Related electronic resource: Current Research at SU : database of SU dissertations, recent titles available full text, 2005. http://wwwlib.umi.com/cr/syr/main.
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Hong, Soonyoung. "An effective data mining approach for structure damage identification." Columbus, Ohio : Ohio State University, 2007. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1194903908.
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Mao, Lei. "Frequency-based structural damage identification and dynamic system characterisation." Thesis, University of Edinburgh, 2012. http://hdl.handle.net/1842/7945.
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This thesis studies structural dynamic system identification in a frequency-based framework. The basic consideration stems from the fact that frequencies may generally be measured with higher accuracy than other pertinent modal data such as mode shapes; however only a limited number of frequencies may be measured in the conventional context of natural frequencies. Being able to measure extra frequencies is a key to the success of a frequency-based method. The main part of the thesis is therefore organised around the involvement of the so-called artificial boundary condition (ABC) frequencies to augment the frequency dataset for general structural damage identification. In essence, the ABC frequencies correspond to the natural frequencies of the system with additional pin supports, but may be extracted from specially configured incomplete frequency response function matrix of the original structure without the need of physically imposing the additional supports. In the first part of the research, a particular focus is placed on the actual extraction of these ABC frequencies from physical experiments through effective modal testing, data collection, data processing and analysis. The influences of key processes involved in a typical modal experimental procedure, including high-fidelity measurement of the (impact) excitation input, averaging, windowing, and an effective use of post-processing techniques, particularly the Singular Value Decomposition (SVD) technique, are scrutinised in relation to the extraction of the ABC frequencies. With appropriate implementation of testing and data processing procedures, results demonstrate that all one-pin and two-pin ABC frequencies from the first few modes can be extracted with good quality in a laboratory setting, and the accuracy of extracted ABC frequencies is comparable to natural frequencies of corresponding orders. A comprehensive study is then carried out to investigate the sensitivities of ABC frequencies to damages. Two-pin ABC frequency sensitivity is formulated by extending the expression of anti-resonance sensitivity. On this basis, the mode shape contribution is adopted as a criterion for the selection of more sensitive ABC frequencies to be employed in detailed parameter identification or finite element model updating procedures. The soundness of using ABC frequencies in structural parameter identification and the effectiveness of the above ABC frequency selection method are subsequently examined through case studies involving laboratory experiments and the corresponding FE model updating. Furthermore, a preliminary study is carried out to examine the possibility of formulating ABC frequency-based damage indicator, herein with an analogy to the mode shape curvature, for direct damage assessment. As an extended investigation in the general framework of frequency-based dynamic identification, in the last part of the thesis, a complex dynamic system, namely a railway bridge under moving loads & masses, is evaluated with regard to the various frequency characteristics involved. The variation of the natural frequencies of the bridge-moving mass system, as well as the presence of the apparent frequencies from the trainloads, are analysed in detail. Besides simplified theoretical analysis, a computational model is developed to simulate the combined bridge-moving vehicle/train system, where the vehicle mass is coupled with the bridge via surface contact. The model is verified by comparison with field measurement data and theoretical predictions. Parametric studies enable a clear identification of the correlation of the frequency contents between the response and the trainload, and provide new insight into the significance of the so-called driving and dominant frequencies. It is found that much of the dynamic response phenomena, including the resonance effect, may be explained from the view point of the frequency characteristics of the trainload pattern, which is governed primarily by the ratio between the carriage length and the bridge length. Finally, a resonance severity indicator (the Z-factor) is developed for the assessment of the resonance effect in the railway bridge response when the trainload moves at a resonance speed. Numerical results demonstrate that the proposed methods are effective for the determination of the critical speed and the resonance effects, including the situations where a significant carriage mass is incorporated.
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Bisht, Saurabh Singh. "Vibration Measurement Based Damage Identification for Structural Health Monitoring." Diss., Virginia Tech, 2010. http://hdl.handle.net/10919/77301.
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The focus of this research is on the development of vibration response-based damage detection in civil engineering structures. Modal parameter-based and model identification-based approaches have been considered. In the modal parameter-based approach, the flexibility and curvature flexibility matrices of the structure are used to identify the damage. It is shown that changes in these matrices can be related to changes in stiffness values of individual structural members. Using this relationship, a method is proposed to solve for the change in stiffness values. The application of this approach is demonstrated on the benchmark problem developed by the joint International Association of Structural Control and American Society of Civil Engineers Structural Health Monitoring task group. The proposed approach is found to be effective in identifying various damage scenarios of this benchmark problem. The effect of missing modes on the damage identification scheme is also studied.
The second method for damage identification aims at identifying sudden changes in stiffness for real time applications. It is shown that the high-frequency content of the response acceleration can be used to identify the instant at which a structure suffers a sudden reduction in its stiffness value. Using the Gibb's phenomenon, it is shown why a high-pass filter can be used for identifying such damages. The application of high-pass filters is then shown in identifying sudden stiffness changes in a linear multi-degree-of-freedom system and a bilinear single degree of freedom system. The impact of measurement noise on the identification approach is also studied. The noise characteristics under which damage identification can or cannot be made are clearly identified. The issue of quantification of the stiffness reduction by this approach is also examined. It is noted that even if the time at which the reduction in stiffness happens can be identified, the quantification of damage requires the knowledge of system displacement values. In principle, such displacements can be calculated by numerical integration of the acceleration response, but the numerical integrations are known to suffer from the low frequency drift error problems. To avoid the errors introduced due to numerical integration of the acceleration response, an approach utilizing the unscented Kalman filter is developed to track the sudden changes in stiffness values. This approach is referred to as the adaptive unscented Kalman filter (AUKF) approach. The successful application of the proposed AUKF approach is shown on two multi-degree of freedom systems that experience sudden loss of stiffness values while subjected to earthquake induced base excitation.Ph. D.
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Al-Ghalib, A. A. "Damage and repair identification in reinforced concrete beams modelled with various damage scenarios using vibration data." Thesis, Nottingham Trent University, 2013. http://irep.ntu.ac.uk/id/eprint/274/.
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This research aims at developing a novel vibration-based damage identification technique that can efficiently be applied to real-time large data for detection, classification, localisation and quantification of the potential structural damage. A complete testing procedure of the Experimental Modal Analysis (EMA) in freely supported beam based on impact hammer, as a relevant excitation source for field measurements, was established and the quality of its measurements was ensured. The experimental data in this research was collected from five laboratory-scale reinforced concrete beams modelled with various ranges of common defects. Reliable finite element beam models for the five beams in their normal conditions were developed correlated and updated using the results of the experimental tests. As a first round of investigation of the damage identification methods, the results of the modal parameters along with a number of their formulations and combinations were evaluated as model-based damage characterisation systems. Different ways for the representation and visualisation of the measurements in the time- or frequency-domain in a format pertinent for pattern identification were assessed. A two-stage combination between principal component analysis and Karhunen-Loéve transformation (also known as canonical correlation analysis) was proposed as a statistical-based damage identification technique. The suggested technique attempts to detect features regarding outliers or variation in the structural dynamic behaviour. In addition, it is used to serve as an unsupervised classification tool for data representing different structural conditions. Vibration measurements from time- and frequency-domain were tested as possible damage-sensitive features in an effort to avoid the expensive prolonged calculations of the modal parameters. In the first stage of the algorithm, principal component analysis is conducted on data from frequency response functions or response power spectral density functions in order to reduce the size of the data. The first prominent principal components that account for a reasonable percentage of the variance in the original data are preserved. In the second stage, the important principal components are provided as inputs to Karhunen-Loéve transformation to constitute the new transformed space. Within-class and between-class covariance matrices are exploited for maximising the discriminant capacity between subgroups. The new generated sets of data are analysed as a typical mathematical eigenproblem to account for the first two or three principal components that retain the major part of the variance. These components are next being employed for significant visualisation of the original data. The proposed system would provide unsupervised means that is capable to process, compare and discriminate between different periodically-collected immense data without considerable unnecessary effort for computations and modelling. The results of this statistical system help in distinguishing between normal and damaged patterns in structural vibration data. Most importantly, the system further dissects reasonably each main group into subgroups according to the levels of damage. The performance of this technique was credibly tested and verified on real measurements collected from the five beams with various detailed damage states. Its efficiency was conclusively proved on data from both frequency response functions and response-only functions. The outcomes of this two-stage system show realistic detection and classification and outperform results from the rival principal component analysis-only.
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Salehian, Armaghan. "Identifying the location of a sudden damage in composite laminates using wavelet approach." Link to electronic thesis, 2003. http://www.wpi.edu/Pubs/ETD/Available/etd-0711103-155908.
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Ravichandran, Aravindh Srivatsav. "Identification and location of sunken logs using sidescan sonar technology." Master's thesis, Mississippi State : Mississippi State University, 2005. http://sun.library.msstate.edu/ETD-db/ETD-browse/browse.
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FILHO, HELIOS MALEBRANCHE OLBRISCH FRERES. "OPTIMAL SENSORS LOCATION FOR FILTERING AND IDENTIFICATION OF DISTRIBUTED SYSTEMS." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 1987. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=8107@1.
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CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOEste trabalho trata do problema não-linear de estimação simultânea de parâmetros e estado, em sistemas distribuídos, e ainda do problema de localização de sensores associado. A classe de modelos em que estamos interessados é caracterizada por operadores lineares, não- limitados, densamente definidos e dissipativos. Nossa abordagem aplica técnicas de filtragem linear a uma seqüência de linearizações em torno de trajetórias convenientemente escolhidas. A localização ótima de sensores é feita de modo a minimizar uma medida do erro da estimatição simultânea de parâmetros e estados. A contribuição original desta tese compreende o desenvolvimento de : (1) um algoritmo que realiza simultaneamente a identificação e a filtragem de uma classe de sistemas distribuídos operando em ambiente estocástico, e (2) um esquema eficiente de localização ótima de sensores para o problema acima mencionado. Alguns exemplos simulados são apresentados com o objetivo de ilustrar os resultados aqui desenvolvidos
This thesis deals with the nonlinear problem of simultaneous parameter and state estimation for distributed systems, including the associated optimal sensor location. The class of models under consideration is caracterrized by linear unbounded operators which are densely defined and dissipative. Our approach applies linear filtering techniquess to a sequence of linearizations at suitable trajectories. The optimal sensors location is carried out by minimizing a meassure of the state and parameter estimation error. The contribution of this thesis comprises: (1) an algorithm for simultaneous identification and filtering for a classs of distributed systems operting in a stochastic environment and (2) an efficient optimal sensors location scheme for the above mentioned problem. Some simulated exemples are presented to illustrate the proposed approach.
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Hyung, Sang Su. "Nondestrutive damage detection by simultaneous identification of stiffness and damping." [College Station, Tex. : Texas A&M University, 2007. http://hdl.handle.net/1969.1/ETD-TAMU-2472.
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Oyarzo, Vera Claudio Andr��s. "Damage identification of unreinforced masonry structures based on vibration response." Thesis, University of Auckland, 2012. http://hdl.handle.net/2292/19371.
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This thesis presents the findings of an investigation on the dynamic characterization of unreinforced masonry (URM) buildings and the use of their distinctive modal properties in identifying damage. Numerical and physical models were used to analyse the applicability of system and damage identification techniques to non-slender URM buildings. Modal tests were conducted on two undamaged URM panels and an undamaged model of a one-storey URM house. Impacts with a calibrated hammer were used to excite the specimens during the modal test, and also horizontal harmonic excitations in the case of the house model. Two system identification techniques (SSI and FDD) were considered for extracting the modal properties. The experimental results were then compared with numerical predictions obtained from finite element models, originally generated based on geometrical and mechanical properties obtained by standardized tests. The numerical predictions were improved by applying sensitivity-based model updating techniques. The evolution of the modal properties of the URM panels and house model due to damage artificially induced were also investigated. Vibration-based and model updating-based damage identification techniques were employed to detect the damage distribution in the specimens. Finally, a seismic assessment was conducted on a typical New Zealand URM building by applying time-history analysis on finite element models. An original seismic hazard zonation and methodology for selecting appropriate ground-motion records in the North Island of New Zealand is described. A typical stand-alone two-storey URM building was simulated using different finite element models. Material and geometrical properties estimated from traditional standardized test results, and properties estimated by a process of model updating based on the experimental data recorded in the vibration tests were considered for these models. The finite element models were analysed using a time-history methodology for a building in Auckland and Wellington. The response of the building was compared with admissible limits established based on a stability criteria, taking into account three levels of intensity for the ground motion.
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Bakhary, Norhisham. "Structural condition monitoring and damage identification with artificial neural network." University of Western Australia. School of Civil and Resource Engineering, 2009. http://theses.library.uwa.edu.au/adt-WU2009.0102.
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Many methods have been developed and studied to detect damage through the change of dynamic response of a structure. Due to its capability to recognize pattern and to correlate non-linear and non-unique problem, Artificial Neural Networks (ANN) have received increasing attention for use in detecting damage in structures based on vibration modal parameters. Most successful works reported in the application of ANN for damage detection are limited to numerical examples and small controlled experimental examples only. This is because of the two main constraints for its practical application in detecting damage in real structures. They are: 1) the inevitable existence of uncertainties in vibration measurement data and finite element modeling of the structure, which may lead to erroneous prediction of structural conditions; and 2) enormous computational effort required to reliably train an ANN model when it involves structures with many degrees of freedom. Therefore, most applications of ANN in damage detection are limited to structure systems with a small number of degrees of freedom and quite significant damage levels. In this thesis, a probabilistic ANN model is proposed to include into consideration the uncertainties in finite element model and measured data. Rossenblueth's point estimate method is used to reduce the calculations in training and testing the probabilistic ANN model. The accuracy of the probabilistic model is verified by Monte Carlo simulations. Using the probabilistic ANN model, the statistics of the stiffness parameters can be predicted which are used to calculate the probability of damage existence (PDE) in each structural member. The reliability and efficiency of this method is demonstrated using both numerical and experimental examples. In addition, a parametric study is carried out to investigate the sensitivity of the proposed method to different damage levels and to different uncertainty levels. As an ANN model requires enormous computational effort in training the ANN model when the number of degrees of freedom is relatively large, a substructuring approach employing multi-stage ANN is proposed to tackle the problem. Through this method, a structure is divided to several substructures and each substructure is assessed separately with independently trained ANN model for the substructure. Once the damaged substructures are identified, second-stage ANN models are trained for these substructures to identify the damage locations and severities of the structural ii element in the substructures. Both the numerical and experimental examples are used to demonstrate the probabilistic multi-stage ANN methods. It is found that this substructuring ANN approach greatly reduces the computational effort while increasing the damage detectability because fine element mesh can be used. It is also found that the probabilistic model gives better damage identification than the deterministic approach. A sensitivity analysis is also conducted to investigate the effect of substructure size, support condition and different uncertainty levels on the damage detectability of the proposed method. The results demonstrated that the detectibility level of the proposed method is independent of the structure type, but dependent on the boundary condition, substructure size and uncertainty level.
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He, Xianfei. "Vibration-based damage identification and health monitoring of civil structures." Diss., Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 2008. http://wwwlib.umi.com/cr/ucsd/fullcit?p3289036.
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Thesis (Ph. D.)--University of California, San Diego, 2008.Title from first page of PDF file (viewed February 5, 2008). Available via ProQuest Digital Dissertations. Vita. Includes bibliographical references.
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Salim, Ali. "The identification of novel methylated proteins in DNA damage response." Thesis, McGill University, 2010. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=86896.
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Protein methylation is a post-translational modification which can take place on both lysine and arginine residues. Classically, the characterization of these modifications on histones has shaped the field of epigenetics. These modifications are regulated by enzymes which specifically catalyze the transfer of a methyl group from a methyl donor to the amino groups of lysine or arginine residues. Methylation of non-histone proteins has also been proven to be crucial in many cellular processes. Understanding the role that protein methylation plays in DNA damage has elucidated the function of many proteins involved in the complex signalling cascade occurring at double-stranded DNA breaks (DSBs). Examining protein methylation has allowed us to identify new proteins implicated in DNA damage and to better clarify the function of existing proteins involved in the DNA damage response. The work presented in this thesis aims to develop new ways to identify methylated proteins involved in DNA damage as well as to verify any functional relevance of newly discovered proteins. Tudor domains traditionally have been shown to bind methylated residues. P53-binding protein 1 (53BP1) is a prominent mediator of DNA damage response and is recruited to DSBs via its tandem Tudor domain by binding methylated lysine on H4 histone protein. A proteomic screen of 53BP1's Tudor domain showed that it could bind brahma-related gene 1 (BRG1), a critical part of the human chromatin remodelling complex. One of the goals of the work presented in this thesis was to verify any in vivo significance of this interaction and if the chromatin remodelling complex plays a significant role in DNA damage response. The existence of an endogenous interaction was verified by a co-immunoprecipitation of BRG1 with 53BP1. In vivo methylation assay showed that BRG1 does in fact contain methylated residues. I hypothesised that 53BP1 could recruit BRG1 to DNA damage sites via this interaction, however, extensive analyLa méthylation de protéines est une modification post-translationelle qui a lieu sur des résidus de lysine et d'arginine. Classiquement, la caractérisation de ces modifications sur les histones a formé le domaine de l'étude épigénétique en expliquant le règlement de l'expression des gènes. Ces modifications sont réglées par les enzymes qui catalysent spécifiquement le transfert d'un groupe méthylique à partir d'un donateur méthylique aux groupes aminés des résidus de lysine ou d'arginine. On s'est également avéré que la méthylation des protéines non-histone est cruciale dans plusieurs des processus cellulaires. Un meilleur arrangement du rôle que la méthylation de protéines joue dans le dommage d'ADN a élucidé la fonction de nombreux protéines impliquées dans une cascade de signalisation complexe se produisant aux cassures double-brin (CDB). L'étude de la méthylation de protéines nous a permise d'identifier des nouvelles protéines impliquées dans le dommage d'ADN et de clarifier la fonction des protéines existantes impliquées dans la réponse au dommage d'ADN. Cette thèse a comme objectif de développer des nouvelles méthodes pour identifier les protéines méthylées impliquées dans le dommage d'ADN et de vérifier la pertinence fonctionnelle des protéines nouvellement découvertes. Les domaines de Tudor traditionnellement ont été démontrés de lier les résidus méthylés. La protéine 53BP1 est une médiatrice de la réponse au dommage d'ADN et est recrutée aux CDBs par l'intermédiaire de son domaine tandem de Tudor en liant la lysine méthylée aux protéines de l'histone H4. Un écran protéomique des domaines de Tudor 53BP1 a prouvé qu'il pourrait lier le gène BRG1, une partie critique de la chromatine humaine transformant le complexe. Un des buts du travail présenté dans cette thèse est de vérifier la signification in vivo de cette interaction et de déterminer si la chromatine transformant le complexe j
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Than, Soe Muang. "Vibration-based finite element model updating and structural damage identification." Thesis, University of Greenwich, 2013. http://gala.gre.ac.uk/11451/.
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Damage and material deterioration could lead to structural failure with unknown consequences. Structural health monitoring strategy based on vibration measurements for existing aging structures offers a promising technique for effectively managing the deteriorating structures. The main objectives of this research are to develop a procedure for finite element model updating by using incomplete modal data identified from vibration measurements, to develop real time structural damage detecting method by directly using vibration measurements and then identify the damage at detailed location and extend in the structure on the basis of the validated numerical model. A steel frame model structure was constructed in the laboratory for finite element model updating and structural damage detection. Forced vibration testing was undertaken on the model structure and dynamic response such as accelerations were measured by using sensors installed. Modal analyses are then carried out to identify modal parameters such as frequencies, mode shapes and damping from the vibration measurements. Structural damage scenarios were simulated by breaking bracing members of the model structure, and modal parameter of the damaged structures were also identified and analysed. An effective approach for directly updating finite element model from measured incomplete modal data with a regularised iterative algorithm is then presented. The exact relationship between the perturbation of structural parameters and the modal properties of the dynamic structure is developed. Numerical simulation investigations and experimental study of a laboratory tested space steel frame model and practical application to the Canton Tower benchmark problem are undertaken to verify the accuracy and effectiveness of the proposed model updating method. Finally, a new approach for real time structural damage detection by using acceleration measurements is presented. Structural damage is characterised at element level by introducing damage parameters which can indicate the location and severity of damage in the structure. The relationship between the damage parameters and the measured dynamic response is then established from the governing equation of the dynamic structure. Numerical examples of cantilever beams, plane frame, and braced frames are adopted to demonstrate the effectiveness of the proposed method. The new proposed technique performs well and produces stable and reliable results, which could be used for real time damage assessment during the event of earthquake and explosion.
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Zhao, Shengjie. "Natural frequency based damage identification of beams using piezoelectric materials." ASME 2015 International Mechanical Engineering Congress and Exposition, 2015. http://hdl.handle.net/1993/31652.
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Following the studies of natural frequency based damage detection methods, an advanced technique for damage detection and localization in beam-type structures using a vibration characteristic tuning procedure is developed by an optimal design of piezoelectric materials. Piezoelectric sensors and actuators are mounted on the surface of the host beam to generate excitations for the tuning via a feedback process. The excitations induced by the piezoelectric effect are used to magnify the effect of the damage on the change of the natural frequencies of the damaged structure to realize the high detection sensitivity. Based on the vibration characteristic tuning procedure, a scan-tuning methodology for damage detection and localization is proposed. From analytical simulations, both crack and delamination damage in the beams are detected and located with over 20% change in the natural frequencies. Finite element method (FEM) simulations are conducted to verify the effectiveness of the proposed methodology.October 2016
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SANTOS, Adam Dreyton Ferreira dos. "Output-only methods for damage identification in structural health monitoring." Universidade Federal do Pará, 2017. http://repositorio.ufpa.br/jspui/handle/2011/9076.
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CNPq - Conselho Nacional de Desenvolvimento Científico e Tecnológico
No campo da monitorização de integridade estrutural (SHM), a identificação de dano baseada em vibração tem se tornado uma área de pesquisa crucial devido a sua potencial aplicação em estruturas de engenharia do mundo real. Assumindo que os sinais de vibração podem ser medidos pelo emprego de diferentes tipos de sistemas de monitorização, quando aplica-se o tratamento de dados adequado, as características sensíveis a dano podem ser extraídas e usadas para avaliar dano estrutural incipiente ou progressivo. Entretanto, as estruturas do mundo real estão sujeitas às mudanças regulares nas condições operacionais e ambientais (e.g., temperatura, umidade relativa, massa de tráfego e outros), as quais impõem dificuldades na identificação do dano estrutural uma vez que essas mudanças influenciam diferentes características de forma distinta. Nesta tese por agregação de artigos, a fim de superar essa limitação, novos métodos output-only são propostos para detectar e quantificar dano em estruturas sob influências operacionais e ambientais não medidas. Os métodos são baseados nos campos de aprendizagem de máquina e inteligência artificial e podem ser classificados como técnicas baseadas em kernel e clusterização. Quando os novos métodos são comparados àqueles do estado da arte, os resultados demonstraram que os primeiros possuem melhor performance de detecção de dano em termos de indicações de dano falso-positivas (variando entre 3,6Ű5,4%) e falso-negativas (variando entre 0Ű2,6%), sugerindo potencial aplicabilidade em soluções práticas de SHM. Se os métodos propostos são comparados entre si, aqueles baseados em clusterização, nomeadamente as abordagens de expectância-maximização global via algoritmos meméticos, provaram ser as melhores técnicas para aprender a condição estrutural normal, sem perda de informação ou sensibilidade aos parâmetros iniciais, e para detectar dano (erros totais iguais a 4,4%).
In the structural health monitoring (SHM) field, vibration-based damage identification has become a crucial research area due to its potential to be applied in real-world engineering structures. Assuming that the vibration signals can be measured by employing different types of monitoring systems, when one applies appropriate data treatment, damage-sensitive features can be extracted and used to assess early and progressive structural damage. However, real-world structures are subjected to regular changes in operational and environmental conditions (e.g., temperature, relative humidity, traffic loading and so on) which impose difficulties to identify structural damage as these changes influence different features in a distinguish manner. In this thesis by papers, to overcome this drawback, novel output-only methods are proposed for detecting and quantifying damage on structures under unmeasured operational and environmental influences. The methods are based on the machine learning and artificial intelligence fields and can be classified as kernel- and cluster-based techniques. When the novel methods are compared to the state-of-the-art ones, the results demonstrated that the former ones have better damage detection performance in terms of false-positive (ranging between 3.65.4%) and false-negative (ranging between 0-2.6%) indications of damage, suggesting their applicability for real-world SHM solutions. If the proposed methods are compared to each other, the cluster-based ones, namely the global expectation-maximization approaches based on memetic algorithms, proved to be the best techniques to learn the normal structural condition, without loss of information or sensitivity to the initial parameters, and to detect damage (total errors equal to 4.4%).
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Emery, Trystan Ross. "Identification of damage in composite materials using thermoelastic stress analysis." Thesis, University of Southampton, 2007. https://eprints.soton.ac.uk/51292/.
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A quantitative damage assessment methodology for composite materials has been achieved using Thermoelastic Stress Analysis (TSA). The TSA technique provides fullfield data which is collected in a non-contacting and real time manner. The damage assessment methodology proposed requires a means of calibrating and temperature correcting the thermoelastic signal; these are developed and presented in this thesis. The thermoelastic theory for calibrating thermoelastic data from orthotropic bodies has traditionally been based on a stress formulation. There are difficulties in calibrating orthotropic materials in this manner and an alternative calibration routine has been devised and validated. The calibration routine provides the thermoelastic theory as a function of strain and permits a simplified calibration route as the laminate strains are the basis and can be measured in a straightforward manner. During damage propagation in laminated structures the specimen heats. The increase in temperature has a significant effect on the thermoelastic data and necessitates that the thermoelastic data be corrected to remove the effect of temperature from the data. A routine is developed that enables the correction of the thermoelastic data in a point-bypoint manner. By combining the strain calibration and temperature correction procedures a damage assessment methodology has been devised. The application of the methodology is demonstrated on glass / epoxy laminate specimens that are fatigue damaged and the damage state assessed using this method; the extent and type of damage is verified qualitatively using visual inspection methods. The work described is applicable to any orthotropic material. The effect of fatigue damage is assessed by periodically collecting thermoelastic data during the specimen life. This data is analysed using damage metrics based on the calibrated strain obtained from the TSA. The wider application of the TSA damage assessment methodology is considered by assessing the ability to locate subsurface damage. A complementary IR technique is used in conjunction with TSA known as Pulse Phase Thermography (PPT). Initial studies demonstrate the ability to resolve the spatial extents of subsurface damage. The purpose of this step is to guide TSA to areas of concern that can subsequently be assessed using the damage metrics to characterise the effect of damage on the residual life of the component. The strain calibration and temperature correction methods that enable TSA to be applied quantitatively to damaged composite materials have not been accomplished prior to this work. They provide novel methods by which TSA data can be assessed, and their application is not restricted to damage studies alone. The ability to temperature correct TSA data has been shown to be of vital importance if thermoelastic data is to be compared in a quantitative fashion. The strain calibration procedure presented will enable thermoelastic studies to be reported quantitatively and expand the application of TSA particularly in validation studies. The damage assessment methodology presented represents a step forward in the application of TSA to the damage assessment of composite materials.
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Elbadawy, Mohamed Mohamed Zeinelabdin Mohamed. "Dynamic Strain Measurement Based Damage Identification for Structural Health Monitoring." Diss., Virginia Tech, 2018. http://hdl.handle.net/10919/86167.
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Structural Health Monitoring (SHM) is a non-destructive evaluation tool that assesses the functionality of structural systems that are used in the civil, mechanical and aerospace engineering practices. A much desirable objective of a SHM system is to provide a continuous monitoring service at a minimal cost with ability to identify problems even in inaccessible structural components. In this dissertation, several such approaches that utilize the measured dynamic response of structural systems are presented to detect, locate, and quantify the damages that are likely to occur in structures. In this study, the structural damage is identified as a reduction in the stiffness characteristics of the structural elements. The primary focus of this study is on the utilization of measured dynamic strains for damage identification in the framed structures which are composed of interconnected beam elements. Although linear accelerations, being more convenient to measure, are commonly used in most SHM practices, herein the strains being more sensitive to elemental damage are considered. Two different approaches are investigated and proposed to identify the structural element stiffness properties. Both approaches are mode-based, requiring first the identification of system modes from the measured strain responses followed by the identification of the element stiffness coefficients. The first approach utilizes the Eigen equation of the finite element model of the structure, while the second approach utilizes the changes caused by the damage in the structural curvature flexibilities. To reduce size of the system which is primarily determined by the number of sensors deployed for the dynamic data collection, measurement sensitivity-based sensor selection criterion is observed to be effective and thus used. The mean square values of the measurements with respect to the stiffness coefficients of the structural elements are used as the effective measures of the measurement sensitivities at different sensor locations. Numerical simulations are used to evaluate the proposed identification approaches as well as to validate the sensitivity-based optimal sensor deployment approach.Ph. D.
All modern societies depend heavily on civil infrastructure systems such as transportation systems, power generation and transmission systems, and data communication systems for their day-to-day activities and survival. It has become extremely important that these systems are constantly watched and maintained to ensure their functionality. All these infrastructure systems utilize structural systems of different forms such as buildings, bridges, airplanes, data communication towers, etc. that carry the service and environmental loads that are imposed on them. These structural systems deteriorate over time because of natural material degradation. They can also get damaged due to excessive load demands and unknown construction deficiencies. It is necessary that condition of these structural systems is known at all times to maintain their functionality and to avoid sudden breakdowns and associated ensuing problems. This condition assessment of structural systems, now commonly known as structural health monitoring, is commonly done by visual onsite inspections manually performed at pre-decided time intervals such as on monthly and yearly basis. The length of this inspection time interval usually depends on the relative importance of the structure towards the functionality of the larger infrastructure system. This manual inspection can be highly time and resource consuming, and often ineffective in catching structural defects that are inaccessible and those that occur in between the scheduled inspection times and dates. However, the development of new sensors, new instrumentation techniques, and large data transfer and processing methods now make it possible to do this structural health monitoring on a continuous basis. The primary objective of this study is to utilize the measured dynamic or time varying strains on structural components such as beams, columns and other structural members to detect the location and level of a damage in one or more structural elements before they become serious. This detection can be done on a continuous basis by analyzing the available strain response data. This approach is expected to be especially helpful in alerting the owner of a structure by identifying the iv occurrence of a damage, if any, immediately after an unanticipated occurrence of a natural event such as a strong earthquake or a damaging wind storm.
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Snyder, Thomas D. "The effects of variability on damage identification with inductive learning." Thesis, Virginia Tech, 1994. http://hdl.handle.net/10919/42160.
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This work discusses the effects of inherent variabilities on the damage identification problem. The goal of damage identification is to detect structural damage before it reaches a level which will detrimentally affect the structure’s performance. Inductive learning is one tool which has been proposed as an effective method to perform damage identification.
There are many variabilities which are inherent in damage identification and can cause problems when attempting to detect damage. Temperature fluctuation and manufacturing variability are specifically addressed. Temperature is shown to be a cause-effect variability which has a measurable effect on the damage identification problem. The inductive learning method is altered to accommodate temperature and shown experimentally to be effective in identifying added mass damage at several locations on an aluminum plate.
Manufacturing variability is shown to be a non-quantifiable variability. The inductive learning method is shown to be able to accommodate this variability through careful examination of statistical significances in dynamic response data. The method is experimentally shown to be effective in detecting hole damage in randomly selected aluminum plates from a manufactured batch.Master of Science
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Magi, Fabrizio. "Vibration fatigue testing for identification of damage initiation in composites." Thesis, University of Bristol, 2016. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.707751.
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Liu, Yu. "The development of a systematic experimental method for damage identification." Thesis, This resource online, 1993. http://scholar.lib.vt.edu/theses/available/etd-06112009-063906/.
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Wang, Ruhua. "Advanced Deep Learning Methods for Vibration-based Structural Damage Identification." Thesis, Curtin University, 2021. http://hdl.handle.net/20.500.11937/86446.
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Vibration-based damage identification has been a challenging task in structural health monitoring. The main difficulty lies on the reliable correlation between the measured vibration characteristics and the damage states of structures. However, the measured vibration signals are often high-dimensional and noise-contaminated, and sometimes in multiple scales or have multiple physical meanings. In this thesis, we propose advanced deep learning models for effective and efficient structural damage identification.
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Nguyen, Khac Duy. "Structural damage identification using experimental modal parameters via correlation approach." Thesis, Queensland University of Technology, 2018. https://eprints.qut.edu.au/117289/2/Khac%20Duy%20Nguyen.pdf.
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This research provides a new damage identification strategy using experimental modal parameters via correlation approach. Two damage identification algorithms using modal strain energy-eigenvalue ratio (MSEE) are presented. Firstly, a method using a simplified term of MSEE called geometric modal strain energy-eigenvalue ratio (GMSEE) is developed. Secondly, the original method is modified using the full term of MSEE, proving better capability of damage identification when used with fewer vibration modes. Performance of the proposed damage identification algorithms has been successfully validated with a numerical model and some experimental models of various scales from small to large.
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Le, Ngoc Thach. "Structural damage identification using static and modal flexibility-based deflections." Thesis, Queensland University of Technology, 2019. https://eprints.qut.edu.au/133428/2/Ngoc_Le_Thesis.pdf.
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This research contributes towards the safe and efficient operation of our infrastructure which are vulnerable to progressive deterioration and damage. Innovative damage detection (DD) methods are proposed herein to detect such damage at the onset to enable appropriate retrofitting and prevent structural failure. These DD methods overcome current difficulties in using popular DD methods based on changes in static and/or modal flexibility-based deflections. First, an innovative deflection-based method is proposed based on explicit relationships between static deflection change and damage characteristics. Next, this method is enhanced for cases where static deflections are estimated indirectly from dynamically measured modal flexibility. The capability of the methods is numerically and experimentally validated for various structures including beams, girder bridges and concrete gravity dams and confirm that the proposed DD methods are reliable to safeguard key civil infrastructure.
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Moradi, Pour Parviz. "An improved modal strain energy method for bridge damage identification." Thesis, Queensland University of Technology, 2020. https://eprints.qut.edu.au/201001/1/Parviz_Moradi%20Pour_Thesis.pdf.
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This thesis improved a modal strain energy (MSE) based damage detection method to detect the damage in bridges. Firstly, an elemental MSE and a sensitivity matrix were mathematically established. Then, it was numerically and experimentally tested on some models such as a fixed-end beam, a three-story frame, the 4-DOF three-story structure of Los Alamos National Laboratory and the I-40 Bridge in New Mexico as a real bridge. The results showed the capability of the proposed method. The research findings will contribute to academic studies and bridge industry to minimize the loss of lives and property by identifying the structural damages.
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Peng, Wu Tseng. "Evaluation of ceramic candle filters degradation and damage location using four-point bending tests." Morgantown, W. Va. : [West Virginia University Libraries], 1999. http://etd.wvu.edu/templates/showETD.cfm?recnum=1105.
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Thesis (M.S.)--West Virginia University, 1999.Title from document title page. Document formatted into pages; contains x, 85 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 81-82).
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Aydogan, Mustafa Ozgur. "Damage Detection In Structures Using Vibration Measurements." Master's thesis, METU, 2003. http://etd.lib.metu.edu.tr/upload/1058809/index.pdf.
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Cracks often exist in structural members that are exposed to repeated loading, which will certainly lower the structural integrity. A crack on a structural member introduces a local flexibility which is a function of the crack depth and location. This may cause nonlinear dynamic response of the structure.
In this thesis, a new method is suggested to detect and locate a crack in a structural component. The method is based on the fact that nonlinear response of a structure with a crack will be a function of the crack location and crack magnitude. The method suggested is the extension of a recently developed technique for identification of non-linearity in vibrating multi degree of freedom
system. In this method, experimentally measured receptances at different forcing levels are used as input, and the existence and location of a nonlinearity are sought.
In order to validate the method, simulated experimental data is used. Characteristics of a cracked beam are simulated by using experimentally obtained analytical expressions, given in the literature. The structure itself is modelled by using finite element method. Several case studies are performed to test and demonstrate the applicability, efficiency and sensitivity of the method suggested. The effect of crack depth on nonlinear system response is also studied in numerical examples.
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Zhang, Muyu [Verfasser], Bernd [Akademischer Betreuer] Markert, and Rüdiger [Akademischer Betreuer] Schmidt. "Auto-correlation-function-based damage index for damage detection and system identification / Muyu Zhang ; Bernd Markert, Rüdiger Schmidt." Aachen : Universitätsbibliothek der RWTH Aachen, 2016. http://d-nb.info/1130327329/34.
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