"In this work an innovative wavelet packet based sifting process for signal decomposition has been developed and its application for health monitoring of time-varying structures is presented. With the proposed sifting process, a signal can be decomposed into its mono-frequency components by examining the energy content in the wavelet packet components of a signal, and imposing certain decomposition criteria. The method is illustrated for simulation data of a linear three degree-of-freedom spring-mass-damper system and the results are compared with those obtained using the empirical mode decomposition (EMD) method. Both methods provide good approximations, as compared with the exact solution for modal responses from a conventional modal analysis. Incorporated with the classical Hilbert transform, the proposed sifting process may be effectively used for structural health monitoring by monitoring instantaneous modal parameters of the structure for both, cases of abrupt structural stiffness loss and progressive stiffness degradation. The effectiveness of this method for practical application is evaluated by applying the methodology for experimental data and the results obtained matched with the field observations. The proposed methodology has shown better results in a comparison study which is done to evaluate performance of the proposed approach with other available SHM techniques, namely EMD technique and Continuous Wavelet Transform (CWT) method, for cases characterized by different damage scenarios and noise conditions."

Ce travail de thèse concerne le contrôle santé intégré (SHM : Structural Health Monitoring) de structures composites aéronautiques par ondes guidées avec des transducteurs piézoélectriques (PZT). La majorité des méthodes de détection classiques reposent sur la comparaison de signaux issus de la structure inspectée à l’état courant avec ceux mesurés dans un état sain (la baseline). La température altère significativement les signaux mesurés et le diagnostic associé si son influence n’est pas prise en compte dans la baseline. D’autre part, l’acquisition de la baseline est très contraignante en vue d’un déploiement des systèmes SHM en condition réelles. La première contribution de cette thèse est l’estimation du champ de température à partir des mesures des PZTs (décalage du spectre fréquentiel et capacité statique), qui permet de compenser l’effet de la température dans la baseline sans ajouter de capteurs dédiés. La seconde contribution concerne les méthodes sans état de référence (baseline free). Les performances de détection de quatre méthodes sont comparées (rupture de réciprocité, variation d’amplitude, analyse des modes de Lamb et baseline instantanée) sur un modèle numérique et des cas expérimentaux d’endommagement à différentes températures sur une plaque de composite fortement anisotrope. Les résultats obtenus démontrent que la décomposition des modes de Lamb dans les signaux mesurés par l’intermédiaire de dual PZTs (PZTs constitués de deux électrodes concentriques – un anneau et un disque – sur leur face supérieure) permet d’améliorer de façon significative les performances de détection de ces méthodes. Un processus de dimensionnement du réseau de dual PZTs est proposé pour le déploiement de ces méthodes sur des structures complexes et prenant en compte la forte anisotropie des matériaux. Ces résultats ouvrent des perspectives prometteuses contribuant potentiellement au transfert des technologies de SHM des laboratoires vers l’industrie. / This thesis work concerns the Structural Health Monitoring (SHM) of aeronautical composite structures by guided waves with piezoelectric transducers (PZT). Conventional detection methods are based on the comparison of signals from the inspected structure in the current state with those measured in a healthy state (the baseline). Temperature significantly alters the measured signals and the associated diagnosis if its influence is not considered in the baseline. Also, the acquisition of the baseline is very constraining for the deployment of SHM systems in real conditions. The first contribution of this thesis is the estimation of the temperature field from the PZT measurements (modal frequency shift and static capacity), which allows to compensate the effect of temperature in the baseline without adding dedicated sensors. The second contribution of this thesis concerns baseline free methods. The detection performance of four methods are compared (reciprocity principle, amplitude variation, Lamb mode analysis and instantaneous baseline) on a numerical model and experimental cases of damages at different temperatures on a highly anisotropic composite plate. The results obtained show that the decomposition of Lamb wave modes in signals measured via dual PZTs (PZTs consisting of two concentric electrodes - a ring and a disk - on their upper side) significantly improves the detection performance of these methods. A dimensioning process for the deployment of these methods on complex anisotropic structures is proposed. These results open up promising opportunities that potentially contribute to the transfer of SHM technologies from laboratories to industry.

Les structures composites sont souvent exposées à des ambiances dynamiques plus oumoins sévères. Ces vibrations peuvent développer différentes formes d’endommagement(fracture des fibres, délamination, fissuration de la matrice. . . ). Les défauts locaux sepropagent et affectent les propriétés mécaniques de la structure modifiant ainsi soncomportement dynamique global. Ces changements peuvent induire une dégradationrapide de la structure et une réduction de sa durée de vie. La thèse a pour objectif lamise en oeuvre de modèles de comportement pour le dimensionnement de structurescomplexes intégrant des sous-structures composites susceptibles d’être endommagées.La méthode des éléments finis est utilisée pour modéliser le comportement vibratoirelinéaire et non-linéaire de ces structures et l’endommagement est introduit via un modèlebilatéral, dans un premier temps. Durant le processus de résolution, une des difficultésrencontrées est le coût de calcul très élevé. Ainsi, un méta-modèle a été développé basésur les réseaux de neurones artificiels couplé avec la méthode de condensation par sousstructurationde Craig-Bampton. Les réseaux de neurones artificiels permettent d’estimer,à moindre cout numérique, le niveau d’endommagement sans avoir recours au calculexact. Le modèle d’endommagement bilatéral n’est pas adapté au cas de chargementsalternés ou périodiques. Par conséquent, la deuxième partie de la thèse est orientée versle développement d’un modèle d’endommagement unilatéral qui donne une meilleuredescription du comportement mécanique lorsque les micro-fissures sont fermées. De plus,dans plusieurs applications industrielles, les structures composites utilisées sont de faibleépaisseur. Par conséquent, elles peuvent avoir naturellement un comportement vibratoirenon-linéaire de type grands déplacements. Le modèle de comportement dynamique engrands déplacements et en présence de la non-linéarité matérielle d’endommagement estdéveloppé et validé. A l’issue de ces travaux de thèse, un outil numérique implémentésur MATLAB® a été développé intégrant deux modèles d’endommagement, bilatéralet unilatéral et une méta-modélisation permettant la localisation et l’estimation del’endommagement ainsi que la prédiction de la réponse dynamique des structures composites, totalement ou localement, endommagées. Le méta-modèle proposé permet deréduire significativement le coût de calcul tout en assurant une bonne précision en termesde localisation et d’estimation du niveau d’endommagement. Cet outil peut s’avérer utilepour diverses applications dans le domaine de surveillance de l’état de santé des structurescomposites. / Composite structures are often exposed to more or less severe dynamic perturbations.These vibrations can develop different forms of damage (fiber fracture, delamination,cracking of the matrix, etc.). Local defects propagate and affect the mechanical propertiesof the structure resulting to modify its global dynamic behavior. These changes can leadto the degradation of the structure and the reduction in its lifetime. This thesis focuseson the implementation of behavior models for the dimensioning of complex structuresintegrating damaged composite sub-structures. The finite element method is used tomodel the linear and nonlinear vibration behavior of these structures where the damageis introduced, initially, via a bilateral model. Since the high computational costs duringthe solving process, a meta-model was developed based on artificial neural networkscoupled with the condensation method of Craig-Bampton. Artificial neural networkspermit to estimate the damage severity at a lower numerical cost without resorting toexact calculation. The bilateral damage model is not adapted to the case of periodic loads.Consequently, the second part of the thesis is oriented towards the development of aunilateral damage model which gives a better description of the mechanical behaviorwhen the micro-cracks are closed. Moreover, in several industrial applications, the usedcomposite structures have small thickness. Therefore, they can naturally have a geometricnon-linear dynamic behavior. The model of dynamic behavior in large displacements andin the presence of material non-linearity of damage is developed and validated. At theend of this thesis, a numerical tool implemented on MATLAB® software was developedintegrating two models of damage, bilateral and unilateral, and a meta-modeling allowingthe localization and the estimation of the damage as well as the prediction of the linear andnon-linear dynamic responses of composite structures, totally or locally, damaged. Theproposed meta-model reduces significantly the computational cost and ensuring a goodaccuracy in terms of localization and estimation of the damage severity. Thereby, thistool can be useful in life-time estimation and monitoring strategies of composite structures.Thèse de

Orientador: Gilberto Pechoto de Melo / Resumo: As metodologias de monitoramento da integridade estrutural baseadas em observadores de estado, em sua grande maioria, utilizam o resíduo obtido a partir da diferença entre a medida e a estimativa de dada resposta dinâmica do sistema para o processo de detecção de danos. Contudo, em determinadas situações, tem-se interesse em realizar o monitoramento através de certa resposta dinâmica que não pode ser medida diretamente. Desta forma, a principal contribuição deste trabalho é propor uma metodologia de detecção de danos para sistemas mecânicos, cujo resíduo é obtido a partir da diferença entre as estimativas do comportamento dinâmico de determinada região do sistema. Estas estimativas são geradas por dois observadores de estado de ordem plena em paralelo, ambos projetados a partir do modelo físico-matemático do sistema em monitoramento sem danos, cujos os ganhos ótimos são determinados pelo método LQR, do inglês Linear Quadratic Regulator. A diferença entre os observadores consiste em serem baseados em conjuntos de medidas distintos. Simulações computacionais são apresentadas para demonstrar a aplicação desta metodologia, de maneira que são discutidas as vantagens e desvantagens em monitorar o sistema utilizando diferentes tipos de força de excitação. Os resultados obtidos são satisfatórios para a detecção dos tipos de dano considerados neste trabalho. / Abstract: Structural health monitoring methodologies based on state observers, for the most part, use the residual obtained from the di erence between the measurement and the estimate of the given dynamic response of the system to the damage detection process. However, in certain situations, it is interesting to carry out the monitoring through a certain dynamic response that can not be measured directly. In this way, the main contribution of this work is to propose a methodology of damage detection for mechanical systems, whose residue is obtained from the di erence between the estimates of the dynamic behavior of a certain region of the system. These estimates are generated by two parallel full-order state observers, both designed from the physical-mathematical model of the monitoring system without damages, whose optimal gains are determined by the LQR (Linear Quadratic Regulator) method. The di erence between observers is that they are based on di erent sets of measures. Computational simulations are presented to demonstrate the application of this methodology, so that the advantages and disadvantages of monitoring the system using di erent types of excitation force are discussed. The results obtained are satisfactory for the detection of the types of damage considered in this work. / Mestre

O objetivo deste trabalho é estudar métodos dinâmicos de detecção de dano em vigas, em especial os métodos baseados na variação da flexibilidade medida dinamicamente. Os métodos revisados formam parte das técnicas de Detecção de Dano Não Destrutivas (DDND). Nas técnicas DDND o dano é localizado por comparação entre o estado sadio e o danificado da estrutura. Neste trabalho, o problema de vibração inverso é apresentado e a matriz de flexibilidade estática da estrutura é determinada a partir de seus parâmetros modais. Com ajuda de um Modelo de Elementos Finitos (MEF) são mostrados os diferentes padrões de variação da matriz de flexibilidade produzidos pela presença do dano. Baseando-se nestes padrões é possível identificar a posição do dano dentro da estrutura, como indicado pelos diversos exemplos apresentados. / The purpose of this work is to study dynamic methods for damage detection in beam structures. The attention is devoted to the methods based on dynamically measured flexibility. The reviewed methods are part of Nondestructive Damage Detection techniques (NDD). In the NDD techniques the damage is determined through the comparison between the undamaged and damaged state of the structure. In this work the inverse vibration problem is presented and the structure\'s flexibility matrix calculated from his modal parameters. The Finite Elements Model (FEM) is employed to show that a clear pattern exist for the changes in the flexibility matrix produced due to the presence of damage. The flexibility matrix changes is used to identify and locate damage as indicated by the several examples presented.

North American civil infrastructures are aging. According to recent (2016) Canadian infrastructure report card, 33% of the Canadian municipal infrastructures are either in fair or below fair condition. The current deficit of replacing fair and poor municipal bridges (covers 26% of bridges) is 13 billion dollars. According to the latest report (2017) by American Society of Civil Engineers, the entire American infrastructure have been given a D+ condition rating. This includes some of the structural elements of infrastructures that pose a significant risk and there is an urgent need for frequent and effective inspection to ensure the safety of people. Visual inspection is a commonly used technique to detect and identify surface defects in bridge structures as it has been considered the most feasible method for decades. However, this currently used methodology is inadequate and unreliable as it is highly dependent on subjective human judgment. This labor-intensive approach for inspection requires huge investment in terms of an arrangement of temporary scaffoldings/permanent platforms, ladders, snooper trucks, and sometimes helicopters. To address these issues associated with visual inspection, the completed research suggests three innovative methods; 1) Combined use of Fuzzy logic and Image Processing Algorithm to quantify surface defects, 2) Unmanned Aerial Vehicle (UAV)-assisted American Association of State Highway and Transportation Officials (AASHTO) guideline-based damage assessment technique, and 3) Patent-pending multi-device robotics-based sensor data acquisition system for mapping and assessing defects in civil structures. To detect and quantify subsurface defects such as voids and delamination using a UAV system, another patent-pending UAV-based acoustic method is developed. It is a novel inspection apparatus that comprises of an acoustic signal generator coupled to a UAV. The acoustic signal generator includes a hammer to produce an acoustic signal in a structure using a UAV. An outcome of this innovative research is the development of a model to refine multiple commercially available NDT techniques’ data to detect and quantify subsurface defects. To achieve this, a total of nine 1800 mm × 460 mm reinforced concrete slabs with varying thicknesses of 100 mm, 150 mm and 200 mm are prepared. These slabs are designed to have artificially simulated defects like voids, debonding, honeycombing, and corrosion. To determine the performance of five NDT techniques, more than 300 data points are considered for each test. The experimental research shows that utilizing multiple techniques on a single structure to evaluate the defects, significantly lowers error and increases accuracy compared to that from a standalone test. To visualize the NDT data, two-dimensional NDT data maps are developed. This work presents an innovative method to interpret NDT data correctly as it compares the individual data points of slabs with no defects to slabs with simulated damage. For the refinement of NDT data, significance factor and logical sequential determination factor are proposed. / Graduate / 2020-09-06

An automated method in damage state assessment of reinforced concrete columns for the purpose of establishing a rapid and quantitative post-earthquake safety and structural evaluation procedure is proposed. Several techniques from the fields of computer vision and image processing are employed in order to develop a set of methods capable of automatically detecting spalled regions on the surface of reinforced concrete columns as well as the properties of cracks and spalled regions on these surfaces. The resulting properties of the observed visible damage on the reinforced concrete column surfaces are then utilized to automatically estimate the existing condition and safety of the column. The damage state is quantified according to the maximum drift capacity of the column. The methods proposed in this research were implemented in a Microsoft Visual Studio .NET environment, and tested on real images of damaged columns. The test results indicated that the methods could automatically detect spalled regions and retrieve the properties of spalling and cracks on reinforced concrete column surfaces in images or video frames, and further, that this retrieved information could be accurately translate to a meaningful assessment of the column's existing damage state in the form of the maximum drift capacity.

In this study, a combined genetic algorithm and non-linear optimisation system is designed and used in the identification of structural damage of a cantilever isotropic beam regarding its location and severity. The vibration-based features, both natural frequencies (i.e. eigenvalues) and displacement mode shapes (i.e. eigenvectors) of the structure in the first two out of plane bending modes, are selected as damage features for various types of damage comprising saw-cut and impact. For this purpose, commercial finite element modelling (FEM) and analysis software Msc. Patran/Nastran&reg / is used to obtain the aforementioned features from intact and damaged structures. Various damage scenarios are obtained regarding saw-cut type damage which is modelled as change in the element thicknesses and impact type damage which is modelled as a reduction of the elastic modulus of the elements in the finite element models. These models are generated by using both 1-D bar elements and 2-D shell type elements in Msc. Patran&reg / and then normal mode analyses are performed in order to extract element stiffness and mass matrices by using Msc. Nastran&reg / . Sensitivity matrices are then created by changing the related properties (i.e. reduction in elastic modulus and thickness) of the individual elements via successive normal mode analyses. The obtained sensitivity matrices are used as coefficients of element stiffness and/or mass matrices to construct global stiffness and/or mass matrices respectively. Following this, the residual force vectors obtained for different damage scenarios are minimised via a combined genetic algorithm and non-linear optimisation system to identify damage location and severity. This minimisation procedure is performed in two steps. First, the algorithm tries to minimise residual force vector (RFV) by only changing element stiffness matrices by aiming to detect impact type damage, as elastic modulus change is directly related to stiffness matrix. Secondly, it performs a minimisation over RFV by changing both element stiffness and mass matrices which aims to detect saw-cut type damage where thickness change is a function of both stiffness and mass matrices. The prediction of the damage type is then made by comparing the objective function value of these two steps. The lowest value (i.e. the fittest) indicates the damage type. The results of the minimisation also provide value of intactness where one representing intact and any value lower than one representing damage severity. The element related to that particular intactness value indicates the location of the damage on the structure. In case of having intactness values which are lower than one in value at various locations shows the existence of multi damage cases and provides their corresponding severities. The performance of the proposed combined genetic algorithm and non-linear optimisation system is tested on various damage scenarios created at different locations with different severities for both single and multi damage cases. The results indicate that the method used in this study is an effective one in the determination of type, severity and location of the damage in beam-like structures.

No matter how inspection techniques have been advanced, manual visual inspection is currently still the first and fundamental step in assessing civil infrastructure. If no sign of deterioration has been spotted in manual inspection, any future inspection actions is not necessary to take. However, manual inspection has been identified with several limitations including the qualitative nature of inspection results, the time-consuming inspection process, and the heavy reliance on inspectors' and/or engineers' experience. In order to overcome these limitations, automated visual inspection systems have been proposed to enhance and/or replicate the manual inspection process. A number of image processing methods have been developed in detecting defects (i.e. coating rusts) and damage (i.e. cracks) on civil infrastructure. Their effectiveness has been verified in inspecting structures, such as bridges, underground pipes, and tunnels. Although existing methods are effective in finding defects and damage from digital images, missing two important links limits their application for rapid infrastructure assessment and rehabilitation. The first link is the correlation between the defects/damage and the structural members that the defects/damage lie on. The second link is the relationship between the defects/damage and their impacts on the structural members. The purpose of this research is to investigate the way of establishing these two links. It is focused on the retrieval of critical structural members and defects/damage information from images/videos, and then the utilization of this information for automated and rapid assessment and rehabilitation of civil infrastructure. Specifically, a combination of techniques from the areas of visual pattern recognition, digital filtering, and machine vision have been used in order to develop a set of methods for concrete column recognition, crack properties retrieval, and air pockets and discoloration detection and evaluation. The methods proposed in this research were implemented in a Microsoft Visual Studio environment, and tested on the real images/videos of concrete structures inflicted with cracks, air pockets and discoloration. The test results indicated that the methods could automatically recognize concrete columns, correctly measure the properties of the cracks in a crack map, and accurately evaluate the impacts of air pockets and discoloration on the visual quality of concrete surfaces.

The thesis addresses the problem of structural damage detection using inverse sensitivity based methods. The focus here is on characterization with regard to identification, location, and, quantification of structural damage in linear time invariant (LTI) systems, using vibration data. The study encompasses both analytical and experimental methods. A suite of five algorithms for damage detection, namely, inverse eigensensitivity method that is refined to account for cross orthogonality between distinct modes, damping dependent eigensolutions, and sensitivity with respect to points of antiresonance and minima, inverse FRF method that includes refinements in terms of inclusion of second order sensitivity, response function method (RFM) based on first order Taylor’s expansion, a newly proposed inverse sensitivity method based on singular values of FRF matrix, and method based on response time histories, are presented. The scope of these methods vis-à-vis the need for model reduction, ability to deal with incomplete data, ill-posedness of governing equations and the need for regularization, sensitivity with respect to measurement noise, ability to identify damping characteristics, the highest and lowest magnitudes of changes in structural properties, and the ability to characterize systems with closely spaced natural frequencies that the methods can detect are discussed. The performance of proposed procedures is illustrated by considering a five degrees-of-freedom (dof) mass-spring-dashpot system and subsequently applied on three archetypal structural systems using analytical and experimental methods. In the examples presented, factors, such as, completeness of measured data in time and frequency, nature (proportional/non-proportional) and magnitude of damping, levels of changes in structural properties, modal truncations, number of governing equations for system parameters, and efficacy of regularization techniques are investigated. The study also highlights the difficulties in implementing the damage detection algorithm based on real life noisy vibration data. A comparative study on the suitability of each of these methods in locating and quantifying of different damage scenarios has been reported. A critical review of performance of the various methods is presented. The thesis concludes with a summary on the contributions made and also deliberates on future avenues for research and development in this area of research.