Nesta tese doutoral estudam-se formas de resolver o problema de detecção de dano em estruturas a partir da aplicação de técnicas de inteligência computacional e da resposta dinâmica da estrutura. Duas opções para a formulação do problema são consideradas. Primeiro, um problema de otimização é estabelecido a partir da minimização da diferença entre os parâmetros dinâmicos experimentais da estrutura na condição com dano e aqueles calculados utilizando um modelo de elementos finitos que representa tal condição. Diferentes técnicas metaheurísticas (algoritmos genéticos, particle swarm optimization, evolução diferencial), algumas em versões com adaptação de parâmetros, são empregadas. Estuda-se, ainda, a formulação do problema de otimização como um com múltiplos objetivos. Uma nova forma de avaliar o desempenho de uma metodologia de detecção de dano é proposta, que está baseada na capacidade da metodologia para obter um nível determinado de exatidão no cálculo da extensão do dano e na presença de falso-negativos e falso-positivos nos resultados. Segundo, aplicam-se redes neurais para determinar o mapeamento entre os parâmetros dinâmicos experimentais da condição atual da estrutura e a extensão ou posição do dano nesta. Estruturas do tipo viga e treliça foram submetidas a diferentes cenários de dano com o intuito de determinar o desempenho das metodologias propostas. Resultados mostram a habilidade de técnicas de inteligência computacional para detecção de cenários de dano com uns poucos elementos danificados; porém não é possível garantir que as metodologias terão sucesso para o 100% dos casos. Recomenda-se a utilização de técnicas de busca local para melhorar a solução encontrada pelos algoritmos globais. Finalmente, observou-se que se requer da determinação da quantidade mínima de informação a ser utilizada, uma função objetivo adequada e uma alta qualidade nas medições para garantir uma detecção de dano confiável. / This research aims at studying how to solve the damage detection problem by using computational intelligence techniques and the dynamic response of the structure. Two different ways for formulating the solution to the problem are implemented. In first place, an optimization problem is formulated as the minimization of the difference between the experimental dynamic parameters for the current structure and those from a finite element model that represent the damaged condition. Several metaheuristics (genetic algorithms, particle swarm optimization and differential evolution) are used to solve the optimization problem, where most of them present adaptive configurations. The implication of a multi-objective approach is also studied. A new scheme to determine the algorithm´s performance is proposed, which computes three error indicators concerning differences between the real and computed damage extents and the presence of false-positives and false-negatives. In second place, artificial neural networks are used to determine the mapping between the experimental dynamic parameters and either the damage extension (quantification) or the damage position (localization). Different damage scenarios were simulated in beam and truss structures to verify the performance of the proposed methodologies. Results show the ability of computational intelligence techniques to detect damage scenarios with a few damaged elements; however, it is not possible to guarantee a 100% of success. It is suggested to use local search techniques to improve the solution found by the different proposed algorithms. Three main conclusions are the followings: i) it is necessary to determine the minimum quantity of modal data that permits guarantying a reliable damage detection, ii) objective functions plays a very important role to the success of the algorithms and iii) noise prejudice the damage identification process.

Vibration-based damage identification (VBDI) techniques have been developed in part to address the problems associated with an aging civil infrastructure. To assess the potential of VBDI as it applies to highway bridges in Iowa, three applications of VBDI techniques were considered in this study: numerical simulation, laboratory structures, and field structures. VBDI techniques were found to be highly capable of locating and quantifying damage in numerical simulations. These same techniques were found to be accurate in locating various types of damage in a laboratory setting with actual structures. Although there is the potential for these techniques to quantify damage in a laboratory setting, the ability of the methods to quantify low-level damage in the laboratory is not robust. When applying these techniques to an actual bridge, it was found that some traditional applications of VBDI methods are capable of describing the global behavior of the structure but are most likely not suited for the identification of typical damage scenarios found in civil infrastructure. Measurement noise, boundary conditions, complications due to substructures and multiple material types, and transducer sensitivity make it very difficult for present VBDI techniques to identify, much less quantify, highly localized damage (such as small cracks and minor changes in thickness). However, while investigating VBDI techniques in the field, a novel methodology, operational response and waveform analysis (ORWA), was developed to extend the focus of traditional VBDI techniques by correlating bridge damage to operational structural motion. It was found that if the frequency-domain response of the structure can be generated from operating traffic load, the structural response can be animated and used to develop a holistic view of the bridge's response to various automobile loadings. By animating the response of a field bridge, concrete cracking (in the abutment and deck) was correlated with structural motion and problem frequencies (i.e., those that cause significant torsion or tension-compression at beam ends) were identified. Furthermore, a frequency-domain study of operational traffic was used to identify both common and extreme frequencies for a given structure and loading. Finally, a finite element analysis of a structure similar to the field bridge was carried out to supplement and partially verify experimental results. Further work should (1) perfect the process of collecting high-quality operational frequency response data; (2) expand and simplify the process of correlating frequency response animations with damage; and (3) develop efficient, economical, pre-emptive solutions to common damage types identified by ORWA.

The use of composite structures in engineering applications has proliferated over the past few decades due to its distinct advantages namely: high structural performance, corrosion resistance, and high strength/weight ratio. However, they also come with a set of disadvantages, i.e. they are prone to fibre breakage, matrix cracking and delaminations. These types of damage are often invisible and if undetected, could lead to catastrophic failures of structures. Although there are systems to detect such damage, the criticality assessment and prognosis of the damage is often much more difficult to achieve. The research study conducted here resulted in the development of a Structural Health Monitoring (SHM) system for a 2D polymeric composite T-joint, used in maritime structures. The SHM system was found to be capable of not only detecting the presence of multiple delaminations in a composite structure, but also capable of determining the location and extent of all t he delaminations present in the T-joint structure, regardless of the load (angle and magnitude) acting on the structure. The system developed relies on the examination of the strain distribution of the structure under operational loading. This SHM system necessitated the development of a novel pre-processing algorithm - Damage Relativity Assessment Technique (DRAT) along with a pattern recognition tool, Artificial Neural Network (ANN), to predict and estimate the damage. Another program developed - the Global Neural network Algorithm for Sequential Processing of Internal sub Networks (GNAISPIN) uses multiple ANNs to render the SHM system independent to variations in structural loading and capable of estimating multiple delaminations in composite T-joint structures. Upto 82% improvement in detection accuracy was observed when GNAISPIN was invoked. The Finite Element Analysis (FEA) was also conducted by placing delaminations of different sizes at various locations in two structures, a composite beam and a T-joint. Glass Fibre Reinforced Polymer T-joints were then manufactured and tested, thereby verifying the accuracy of the FEA results experimentally. The resulting strain distribution from the FEA was pre-processed by the DRAT and used to trai n the ANN to predict and estimate damage in the structures. Finally, on testing the SHM system developed with strain signatures of composite T-joint structures, subjected to variable loading, embedded with all possible damage configurations (including multiple damage scenarios), an overall damage (location & extent) prediction accuracy of 94.1% was achieved. These results are presented and discussed in detail in this study.

Introduction: This study sought to investigate the effects of soft tissue on measurements of a spinal vibration response using skin-mounted accelerometers and a non-invasive contact tip. Methods: Vibration was applied to the spine of porcine and human cadavers. Measurements of the spinal vibration response were taken from needle, skin, and bone-mounted accelerometers. Several skin-mounted accelerometer placements dorsal to a spinous process were tested, and 6 different non-invasive contact tip shapes were used to explore sources of variance in the signals. Results: Vibration measured from skin-mounted accelerometers had altered signal patterns compared to bone-mounted accelerometers. The measured FRF was found to be sensitive to accelerometer positioning. No significant difference in skin-bone correlation was attributed to contact tip shape or vertebral level. Conclusion: The use of a non-invasive contact tip excites vibration in the soft tissues which overlay the spine, in addition to the vertebral column. This vibration interferes with skin sensor measurements of vertebral vibration response, with the effect diminishing as distance from the contact tip increases. Small changes in contact tip shape do not affect the correlation between skin and bone signals.

Cette thèse a pour but didentifier de changements dans le comportement dynamique dun système mécanique par le développement des techniques didentification, de détection et de recalage de modèle. Un endommagement ou une activation de non - linéarité est considéré responsable du changement. Une bien connue classification pour la détection dendommagement dans la littérature est utilisée dans la thèse, qui définit quatre niveaux dans lordre croissant de complexité: - Niveau 1 : Détection dendommagement : inspection de la présence dendommagement dans la structure. - Niveau 2 : Localisation dendommagement : détermination de position de lendommagement. - Niveau 3 : Evaluation de la gravité de lendommagement. - Niveau 4 : Prévision de la durée restant de vie de la structure. Selon la classification décrite ci-dessus, le problème de diagnostic dans cette thèse est abordé pour les trois premiers niveaux, i.e. détection, localisation et évaluation. Lidentification dendommagements ou dactivation de non - linéarité est basée sur une comparaison entre un état actuel et létat de référence (en normal condition). La thèse est organisée comme suit : Chapitre 1 présente une étude bibliographique sur des méthodes dindentification modale et de détection. Cette partie décrit quelques caractéristiques principales de systèmes non - linéaires et également des défis que présente la non - linéarité. Les problèmes de localisation et dévaluation sont discutés ensuite. Chapitres 2, 3 et 4 se concentrent sur la détection de défaut, par exemple lactivation de non linéarité ou lapparition dendommagement par trois méthodes respectivement : la Transformée en ondelettes (Wavelet transform), la Séparation aveugle au second ordre (Second-Order Blind Identification) et lAnalyse en composantes principales à noyau (Kernel Principal component Analysis). Seuls des signaux de sortie sont utilisés pour le traitement. Les deux premières méthodes réalisent la surveillance structurale par un processus didentification modale, tandis que la dernière méthode exerce directement dans des espaces caractéristiques déterminés par une fonction de noyau choisie. La détection peut être réalisée au moyen du concept dangle entre sous-espaces ou basée sur des statistiques. La robustesse des méthodes est illustrée sur une structure de poutre avec une non -linéarité géométrique à un bout ; ce modèle a été étudié dans le cadre dun projet de recherche européenne COST F3. Des autres exemples sont également considérés, tels quune maquette davion avec différents niveaux dendommagement et deux applications industrielles avec le but de contrôle de qualité sur un set dappareils électro - mécaniques et sur des joints de soudure. Chapitre 5 vise à la localisation dendommagement basée sur lanalyse de sensibilité des résultats de lAnalyse en composantes principales dans le domaine fréquentiel. La localisation est exécutée par la comparaison des sensibilités de composantes principales entre létat de référence (saine) et un état endommagé. Seules les réponses mesurées, e.g. réponses en fréquence (FRFs) sont nécessaires pour cet objectif. Après lanalyse de sensibilité au Chapitre 5, Chapitre 6 sadresse à lévaluation de paramètres, par exemple estimation dendommagements. Pour ce but, une procédure de recalage de modèle est exécutée. Cette procédure demande de construire un modèle analytique de la structure. Lanalyse de sensibilité pour la localisation dendommagement est illustrée par des données numériques et expérimentales dans des systèmes de masse - ressort et dans des structures de poutre. Une réelle structure, i.e. le pont I-40 à New Mexico qui a été détruite en 1993 est aussi examinée. Enfin, des conclusions sont retirées basées sur le travail réalisé et quelques perspectives sont proposées pour la continuation de cette recherche.

Vibration-based damage detection (VBDD) comprises a family of non-destructive testing methods in which changes to dynamic characteristics are used to track the condition of a structure. Although VBDD methods have been successfully applied to various mechanical systems and to simple beam-like structures, significant challenges remain in extending this technology to complex, spatially distributed structures such as bridges. <p> In the present study, numerical simulations using a calibrated finite element model were used to investigate the use of VBDD methods to detect small-scale damage on a two-span, integral abutment overpass structure located in Saskatoon, Saskatchewan. The small scale damage was defined in this study as the removal of a concrete element from the top surface of the bridge deck, resembling the spalled clear cover of concrete deck of the overpass. Five different VBDD techniques were evaluated, including the Change in Mode Shape, Change in Flexibility, Change in Mode Shape Curvature, Change in Uniform Flexibility Curvature and Damage index methods. In addition, the influence of the size of damage, the orientation of damage geometry, sensor spacing (3 m, 5 m and 7.5 m), the approach used for mode shape normalization, and uncertainty in the measured mode shapes was investigated. <p> It was found that localized damage could be reliably detected and located if the sensors were located within 3 m of the damage (the distance between adjacent girders) and if uncertainty in the mode shapes was attenuated through the use of a sufficient number of repeated trials. Furthermore, studies using a limited sensor installation that could be achieved without interrupting the flow of traffic indicated that small scale damage could be detected and potentially located using sensors that are placed well away from the damaged area, provided uncertainty in mode shape was attenuated.

Vibration-based damage detection (VBDD) comprises a family of non-destructive testing methods in which changes to dynamic characteristics are used to track the condition of a structure. Although VBDD methods have been successfully applied to various mechanical systems and to simple beam-like structures, significant challenges remain in extending this technology to complex, spatially distributed structures such as bridges. <p> In the present study, numerical simulations using a calibrated finite element model were used to investigate the use of VBDD methods to detect small-scale damage on a two-span, integral abutment overpass structure located in Saskatoon, Saskatchewan. The small scale damage was defined in this study as the removal of a concrete element from the top surface of the bridge deck, resembling the spalled clear cover of concrete deck of the overpass. Five different VBDD techniques were evaluated, including the Change in Mode Shape, Change in Flexibility, Change in Mode Shape Curvature, Change in Uniform Flexibility Curvature and Damage index methods. In addition, the influence of the size of damage, the orientation of damage geometry, sensor spacing (3 m, 5 m and 7.5 m), the approach used for mode shape normalization, and uncertainty in the measured mode shapes was investigated. <p> It was found that localized damage could be reliably detected and located if the sensors were located within 3 m of the damage (the distance between adjacent girders) and if uncertainty in the mode shapes was attenuated through the use of a sufficient number of repeated trials. Furthermore, studies using a limited sensor installation that could be achieved without interrupting the flow of traffic indicated that small scale damage could be detected and potentially located using sensors that are placed well away from the damaged area, provided uncertainty in mode shape was attenuated.

This work investigates the application of homogenization techniques to the dynamic analysis of periodic solids, with emphasis on lattice structures. The presented analysis is conducted both through a Fourier-based technique and through an alternative approach involving Taylor series expansions directly performed in the spatial domain in conjunction with a finite element formulation of the lattice unit cell. The challenge of increasing the accuracy and the range of applicability of the existing homogenization methods is addressed with various techniques. Among them, a multi-cell homogenization is introduced to extend the region of good approximation of the methods to include the short wavelength limit. The continuous partial differential equations resulting from the homogenization process are also used to estimate equivalent mechanical properties of lattices with various internal configurations. In particular, a detailed investigation is conducted on the in-plane behavior of hexagonal and re-entrant honeycombs, for which both static properties and wave propagation characteristics are retrieved by applying the proposed techniques. The analysis of wave propagation in homogenized media is furthermore investigated by means of the bridging scales method to address the problem of modelling travelling waves in homogenized media with localized discontinuities. This multi-scale approach reduces the computational cost associated with a detailed finite element analysis conducted over the entire domain and yields considerable savings in CPU time. The combined use of homogenization and bridging method is suggested as a powerful tool for fast and accurate wave simulation and its potentials for NDE applications are discussed.

In this thesis, a method proposed by Han et al. [40] for detecting and locating damage in a structural member was adapted. The method was based on the energies that were calculated from the CWT coefficients of vibrational response of a cantilever beam. A transverse cut at varying depths was introduced. The presence and location of crack was investigated by processing experimentally acquired acceleration signals. Results of modal analysis and wavelet analysis of the beam with different cut depths were compared. In addition, effect of using different mother wavelets in CWT analysis for damage detection capability was investigated. Acceleration data were analyzed through CWT at different scales and CWT coefficients were calculated. Those CWT coefficients obtained from different scales were evaluated from the standpoint of damage detection. Effectiveness of energy indices associated with CWT coefficients in damage detection was demonstrated as independent of the type of mother wavelet.

This research covers modeling of Electro Magnetic Acoustic Transducers (EMATs) and their application in excitation and detection of longitudinal guided Lamb wave modes for evaluation of flaws in cylindrical pipes. The combination of the configuration of transducers and the frequency of the input current is essential for successful excitation of desired guided wave modes and for proper interpretation of the results. In this study EMATs were successfully constructed and longitudinal modes L(0,1) and L(0,2) were excited in the pipe. From the recorded signals the level of simulated damage in pipes could be assessed. It is also possible to theoretically predict the location of the pipe flaws. Theoretical predictions are matched with experimental results. Dents and holes in pipes are detected by appropriate signal processing of received L(0,1) and L(0,2) modes.