Submitted by Danilo Ecidir Budoya (dbudoya.eng@gmail.com) on 2018-04-25T21:17:47Z No. of bitstreams: 1 Dissertação - Danilo Budoya.pdf: 3474646 bytes, checksum: 301f48ae4a6c065e915f91fe3d764dd8 (MD5) / Approved for entry into archive by Minervina Teixeira Lopes null (vina_lopes@bauru.unesp.br) on 2018-04-26T12:29:49Z (GMT) No. of bitstreams: 1 budoya_de_me_bauru.pdf: 3415870 bytes, checksum: 35422f7801e20a052d2c9a303aa7e2dd (MD5) / Made available in DSpace on 2018-04-26T12:29:49Z (GMT). No. of bitstreams: 1 budoya_de_me_bauru.pdf: 3415870 bytes, checksum: 35422f7801e20a052d2c9a303aa7e2dd (MD5) Previous issue date: 2018-04-20 / Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) / Sistemas de monitoramento de integridade estrutural (SHM – Structural Health Monitoring) são científica e economicamente relevantes como métodos de detecção de danos estruturais em diversos tipos de estruturas, aumentando assim a segurança e reduzindo os custos de manutenção. Entre os vários princípios de detecção de danos, o método da impedância eletromecânica (E/M) baseia-se na medição da impedância elétrica do transdutor piezelétrico fixado à estrutura monitorada. Aqui, a exatidão e precisão do sistema de medição são fundamentais para o diagnóstico correto da estrutura. Portanto, essa dissertação apresenta uma análise comparativa de duas técnicas de medição de impedância para detecção de danos que são tipicamente utilizadas em analisadores de impedância comerciais e em outros sistemas de medição alternativos: medições em estado transitório utilizando um sinal de excitação de varredura e medições em estado estacionário utilizando um sinal senoidal puro para cada frequência de excitação. Os testes foram realizados com cargas resistivas e capacitivas de valores nominais 100 Ω e 10 nF, respectivamente, e com um transdutor piezelétrico fixado em uma barra de alumínio que representa uma estrutura monitorada. As duas técnicas foram comparadas com base na exatidão, precisão, sensibilidade à danos e tempo necessário para as medições. Os resultados destacam as características importantes de cada técnica, as quais devem ser consideradas para o desenvolvimento de sistemas de SHM baseados na impedância e o diagnóstico correto das estruturas monitoradas. / Structural health monitoring (SHM) systems are scientifically and economically relevant as methods of detecting structural damage to various types of structures, thus increasing safety and reducing maintenance costs. Among the various principles of damage detection, the electromechanical impedance (EMI) method is based on the electrical impedance measurement of piezoelectric transducers attached to the monitored structure. Here, the accuracy and precision of the measurement system are fundamental for the correct diagnosis of the structure. Therefore, this dissertation presents a comparative analysis of two impedance measurement techniques for damage detection that are typically used in commercial impedance analyzers and other alternative measurement systems: transient-state measurements using a sweep excitation signal and steady-state measurements using a pure sinusoidal signal for each excitation frequency. Tests were performed with resistive and capacitive loads with nominal values of 100 Ω e 10 nF, respectively, and a piezoelectric transducer fixed to an aluminum bar representing a monitored structure. The two techniques were compared based on the accuracy, precision, sensibility to damage and time required for the measurements. The results highlight the important features of each technique, which should be considered for the development of impedance-based SHM systems and the correct diagnosis of monitored structures. / 2015/23272-1

Resumo: Este trabalho apresenta o estudo e desenvolvimento de uma técnica de monitoramento da integridade estrutural, para identificação e caracterização de falhas estruturais através da metodologia das ondas de Lamb utilizando materiais piezelétricos como sensores e atuadores. Ondas de Lamb são uma forma de perturbação elástica que se propaga guiada entre duas superfícies paralelas livres. Ondas de Lamb são formadas quando o atuador excita a superfície da estrutura com um pulso depois de receber um sinal. Quando uma onda propaga na superfície de uma placa, ela chega em um PZT sensor por diferentes caminhos. Um caminho é quando a onda atinge o sensor diretamente, ou seja, sem obstáculos no caminho em que ela se propaga. Outro caminho possível é quando a onda chega ao sensor após se propagar sobre descontinuidades existentes na superfície da estrutura. Com as várias características dos sinais recebidos, e com o uso de certas técnicas de processamento de sinais, essas falhas podem ser identificadas, realizando-se a ação correta tentando evitar a total falha da estrutura. Nesse contexto, diferentes testes experimentais foram realizados em diferentes tipos de estruturas. Redes de sensores e atuadores piezelétricos foram acopladas na superfície dessas estruturas, a fim de se fazer a configuração das ondas de Lamb. Os PZTs atuadores excitaram a estrutura em altas faixas de frequência. Diferentes tipos de falhas estruturais foram simuladas, através do aumento de massa, alteração de rigidez e através de cortes na borda das estruturas. Quatro índices de falha foram utilizados para detectar a presença da falha na estrutura, são eles: Root- Means-Square Deviation (RMSD), Índice de Falha Métrica (IFM), Norma H2 e Correlation Coefficient Deviation Mean (CCDM). Estes índices foram computados através dos sinais de entrada e de saída no domínio da frequência... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: This work presents the study and development of a Structural Health Monitoring technique for identification and characterization of structural damages based on Lamb waves methodology using piezoelectric materials as actuators and sensors. Lamb waves are a form of elastic perturbation that remains guided between two parallel free surfaces. Lamb waves are formed when the actuator excites the structure's surface with a pulse after receiving a signal. When the wave propagates on the structure, it comes in a PZT sensor from different paths. One path is when the wave reaches the sensor directly, i.e. without obstacles in the path in which it propagated. Another possible path is when the wave reaches the sensor after spreads on discontinuities in the structure's surface. Damages can be detected and located through several features of the received signals and with the use of certain techniques of signal processing. In this context, several experimental tests were performed on different kinds of structures. Piezoelectric actuators and sensors networks were attached on the surface of these structures in order to make the Lamb waves configuration. The PZTs actuators excited the structure in high frequency ranges. Different kinds of structural damages were simulated by increasing mass, reduction of stiffness and cuts through the edge of the structures. Four damage-sensitive indexes were used to detect the presence of the damage in the structure: Root-Means-Square Deviation (RMSD), Metric Damage Index (MDI), H2 Norm and Correlation Coefficient Deviation (CCDM). These indices were computed in the frequency domain. The results showed the viability of the Lamb waves methodology for Structural Health Monitoring system using smart materials as actuators and sensors / Orientador: Vicente Lopes Junior / Coorientador: Michael J. Brennan / Banca: Gilberto Pechoto de Melo / Banca: José Roberto de França Arruda / Mestre

Orientador: Fábio Roberto Chavarette / Resumo: Diante da constante necessidade de avanço tecnológico na agricultura para promover o aumento da produtividade e seguranças aos indivíduos envolvidos no processo, esta pesquisa apresenta o desenvolvimento de um sistema inteligente, utilizando redes neurais artificiais, aplicado ao monitoramento e análise de falhas estruturais em um trator. Simulou-se o trator por meio de um modelo numérico, representado através de equações diferenciais, o qual gera sinais conforme se alteram os parâmetros de velocidade do trator e a distância entre as saliências no solo. Para a análise, identificação e classificação dos dados simulados computacionalmente, foi utilizado uma rede neural do tipo ARTMAP-Fuzzy, que utiliza conceitos da Teoria da Ressonância Adaptativa, cujo algoritmo foi desenvolvido utilizando o programa Matlab. A principal aplicação deste sistema é inspecionar a estrutura do trator objetivando sua melhor conservação, indicando se o mesmo encontra-se em condições normais ou em caso de falha estrutural. Caso uma falha seja detectada, é possível classificar seu tipo. Os resultados evidenciados foram obtidos por meio de média simples entre as execuções do sistema, em virtude de se elevar a veracidade das informações demonstradas. Os resultados obtidos na aplicação da rede neural ao problema especificado mostraram-se ser satisfatórios. / Abstract: Faced with the constant need for technological advancement in agriculture to promote increased productivity and security to individuals involved in the process, this research presents the development of an intelligent system using artificial neural networks applied to the structural health monitoring and analysis of failure on a tractor. The tractor was simulated by means of a numerical model built by differential equations, which generates signals according to the parameters of tractor's speed and the distance between consecutive protrusions on the ground. For the analysis, identification and classification of computationally simulated data, a artificial neural network known as ARTMAP-fuzzy was used, which uses concepts of Adaptive Resonance Theory, whose algorithm was developed using Matlab. The main application of this system is to inspect the tractor structure aiming its better conservation, indicating whether it is in normal conditions or in case of structural failure. If the fault was detected, it is possible to classify the type of failure identified. The disclosed results were obtained by simple average between the executions of the system, because to increase the accuracy of the information shown. The results obtained in the application of artificial neural network to the specified problem proved to be satisfactory. / Mestre

Thesis (MTech (Mechanical Engineering))--Cape Peninsula University of Technology, 2015. / Currently non-destructive testing techniques for composite aircraft structures are disadvantaged when compared to online Structural Health Monitoring (SHM) systems that monitor the structure while in-service and give real time data. The present research work looks at developing a protocol for online structural health monitoring of a UAV wing structure using PVDF film sensors, especially including the monitoring of structural changes caused by defects. Different types of SHM techniques were studied in relation to carbon fibre composites. Laminate composite make-up and manufacturing process was investigated and vacuum infusion process was used to manufacture the samples that resemble the Guardian II wing structure, then the three-point bending test was used to determine the material properties. Digital Shearography was employed as a stationery non-destructive technique to determine the sensor to structure attachment, type and position of defects that affect the state of performance. Finite Element Analysis (FEA) was done using ANSYS Workbench which served as a modelling tool using a drawing imported from Solid-works. Experimental investigation was done using PVDF sensor embedded on the surface of the sample in a cantilever setup and a vertical Vernier scale to measure the deflection due to impact and vibration loading. A Fluke-View oscilloscope was used as a data logger when the measurement of the output voltage and the natural frequency were recorded. The techniques of using FEA and experimental investigation were then compared. The findings of this study showed that the PVDF sensor is suitable for condition monitoring of a UAV wing structure.

Detecção de dano em estruturas de engenharia de grandes dimensões através da análise de suas características dinâmicas envolve diversos campos de estudo. O primeiro deles trata da identificação dos parâmetros modais da estrutura, uma vez que executar testes de vibração livre em tais estruturas não é uma tarefa simples, necessita-se de um método robusto que seja capaz de identificar os parâmetros modais dessa estrutura a ações ambientais, campo esse chamado de análise modal operacional. Este trabalho trata do problema de detecção de dano em estruturas que possam ser representadas através de modelos em pórticos planos e vigas e que estejam submetidos à ação de vibrações ambientais. A localização do dano é determinada através de um algoritmo de otimização conhecido como Backtracking Search Algorithm (BSA) fazendo uso de uma função objetivo que utiliza as frequências naturais e modos de vibração identificados da estrutura. Simulações e testes são feitos a fim de verificar a concordância da metodologia para ambos os casos. Para as simulações, são utilizados casos mais gerais de carregamentos dinâmicos, e dois níveis de ruído (3% e 5%) são adicionados ao sinal de respostas para que esses ensaios se assemelhem aos ensaios experimentais, onde o ruído é inerente do processo. Já nos ensaios experimentais, apenas testes de vibração livre são executados. Diversos cenários de dano são propostos para as estruturas analisadas a fim de se verificar a robustez da rotina de detecção de dano. Os resultados mostram que a etapa de identificação modal estocástica através do método de identificação estocástica de subespaço (SSI) teve ótimos resultados, possibilitando, assim, a localização da região danificada da estrutura em todos os casos analisados. / Damage detection in large dimensions engineering structures through the analysis of their dynamic characteristics involves several fields. The first one deals with the structure modal identification parameter, since running free vibration tests in such structures is not a simple task, robust methods are needed in order to identify the modal parameters of this structure under ambient vibrations, this field is known as operational modal analysis. This work deals with the problem of damage detection in structures under ambient vibrations that can be represented by FEM using frame and beam elements. The damage location is determined through an optimization algorithm know as Backtracking Search Algorithm (BSA). It uses as objective function the identified natural frequencies and modes of vibration of the structure. Numerical and experimental tests are performed to assess the agreement of the methodology for both cases. For the numerical tests, more general cases of dynamic loads are used, and two noise levels (3% and 5%) are added to the response signal to assessing the robustness of the methodology close to the field conditions, in which noise is inherent of the process. In the experimental tests, only free vibration tests are performed. Several damage scenarios are proposed for the analyzed structures to check the robustness of the damage detection routine. The results show that the stochastic modal identification using the stochastic subspace identification (SSI) method had excellent results, thus allowing the location of the damaged region of the structure in all analyzed cases.

abstract: Advancements in mobile technologies have significantly enhanced the capabilities of mobile devices to serve as powerful platforms for sensing, processing, and visualization. Surges in the sensing technology and the abundance of data have enabled the use of these portable devices for real-time data analysis and decision-making in digital signal processing (DSP) applications. Most of the current efforts in DSP education focus on building tools to facilitate understanding of the mathematical principles. However, there is a disconnect between real-world data processing problems and the material presented in a DSP course. Sophisticated mobile interfaces and apps can potentially play a crucial role in providing a hands-on-experience with modern DSP applications to students. In this work, a new paradigm of DSP learning is explored by building an interactive easy-to-use health monitoring application for use in DSP courses. This is motivated by the increasing commercial interest in employing mobile phones for real-time health monitoring tasks. The idea is to exploit the computational abilities of the Android platform to build m-Health modules with sensor interfaces. In particular, appropriate sensing modalities have been identified, and a suite of software functionalities have been developed. Within the existing framework of the AJDSP app, a graphical programming environment, interfaces to on-board and external sensor hardware have also been developed to acquire and process physiological data. The set of sensor signals that can be monitored include electrocardiogram (ECG), photoplethysmogram (PPG), accelerometer signal, and galvanic skin response (GSR). The proposed m-Health modules can be used to estimate parameters such as heart rate, oxygen saturation, step count, and heart rate variability. A set of laboratory exercises have been designed to demonstrate the use of these modules in DSP courses. The app was evaluated through several workshops involving graduate and undergraduate students in signal processing majors at Arizona State University. The usefulness of the software modules in enhancing student understanding of signals, sensors and DSP systems were analyzed. Student opinions about the app and the proposed m-health modules evidenced the merits of integrating tools for mobile sensing and processing in a DSP curriculum, and familiarizing students with challenges in modern data-driven applications. / Dissertation/Thesis / M.S. Electrical Engineering 2013

Submitted by Pedro Barros (pedro.silvabarros@ufpe.br) on 2018-06-26T22:26:10Z No. of bitstreams: 2 license_rdf: 811 bytes, checksum: e39d27027a6cc9cb039ad269a5db8e34 (MD5) DISSERTAÇÃO Caio Bezerra Souto Maior.pdf: 3924685 bytes, checksum: 6968386bf75059f45ee80306322d2a56 (MD5) / Made available in DSpace on 2018-06-26T22:26:10Z (GMT). No. of bitstreams: 2 license_rdf: 811 bytes, checksum: e39d27027a6cc9cb039ad269a5db8e34 (MD5) DISSERTAÇÃO Caio Bezerra Souto Maior.pdf: 3924685 bytes, checksum: 6968386bf75059f45ee80306322d2a56 (MD5) Previous issue date: 2017-02-21 / CAPES / The useful life time of equipment is an important variable related to reliability and maintenance. The knowledge about the useful remaining life of operation system by means of a prognostic and health monitoring could lead to competitive advantage to the corporations. There are numbers of models trying to predict the reliability’s variable behavior, such as the remaining useful life, from different types of signal (e.g. vibration signal), however several could not be realistic due to the imposed simplifications. An alternative to those models are the learning methods, used when exist many observations about the variable. A well-known method is Support Vector Machine (SVM), with the advantage that is not necessary previous knowledge about neither the function’s behavior nor the relation between input and output. In order to achieve the best SVM’s parameters, a Particle Swarm Optimization (PSO) algorithm is coupled to enhance the solution. Empirical Mode Decomposition (EMD) and Wavelets rise as two preprocessing methods seeking to improve the input data analysis. In this paper, EMD and wavelets are used coupled with PSO+SVM to predict the rolling bearing Remaining Useful Life (RUL) from a vibration signal and compare with the prediction without any preprocessing technique. As conclusion, EMD models presented accurate predictions and outperformed the other models tested. / O tempo de vida útil de um equipamento é uma importante variável relacionada à confiabilidade e à manutenção, e o conhecimento sobre o tempo útil remanescente de um sistema em operação, por meio de um monitoramento do prognóstico de saúde, pode gerar vantagens competitivas para as corporações. Existem diversos modelos utilizados na tentativa de prever o comportamento de variáveis de confiabilidade, tal como a vida útil remanescente, a partir de diferentes tipos de sinais (e.g. sinal de vibração), porém alguns podem não ser realistas, devido às simplificações impostas. Uma alternativa a esses modelos são os métodos de aprendizado, utilizados quando se dispõe de diversas observações da variável. Um conhecido método de aprendizado supervisionado é o Support Vector Machine (SVM), que gera um mapeamento de funções de entrada-saída a partir de um conjunto de treinamento. Para encontrar os melhores parâmetros do SVM, o algoritmo de Particle Swarm Optimization (PSO) é acoplado para melhorar a solução. Empirical Mode Decomposition (EMD) e Wavelets são usados como métodos pré-processamento que buscam melhorar a qualidade dos dados de entrada para PSO+SVM. Neste trabalho, EMD e Wavelets foram usadas juntamente com PSO+SVM para estimar o tempo de vida útil remanescente de rolamentos a partir de sinais de vibração. Os resultados obtidos com e sem as técnicas de pré-processamento foram comparados. Ao final, é mostrado que modelos baseados em EMD apresentaram boa acurácia e superaram o desempenho dos outros modelos testados.

Abstract This thesis deals with the developing of fibre-optic instruments for monitoring the health of civil engineering and composite structures. A number of sensors have been tested for use with different road structures, concrete bridges, fibre reinforced polymer (FRP) containers and other composite specimens, the interrogation methods being mainly based on measuring optical power and time-of-flight (TOF). The main focus is on the development of a fibre-optic TOF measurement system and its applications, but different sensing needs and fibre-optic measurement systems are also reviewed, with the emphasis on commercial devices. Deformation in a road structure was studied with microbending sensors of gauge-length about 10 cm and a commercial optical time domain reflectometer (OTDR) in a quasi-distributed fashion. The responses of the optical fibre sensors during the one-year measurement period were similar in shape to those obtained with commercial strain gauges but the absolute measurement values typically deviated by several tens of per cent. Low dynamic range, crosstalk and poor signal-to-noise ratio proved to be the main problem when measuring several successive sensors with an OTDR. In another road investigation, microbending and speckle sensors were found useful for providing on/off-type information for traffic control applications. FRP composite containers were investigated with the focus on developing a continuous monitoring system for improving yield and quality by evaluating the state of cure during the manufacturing process and for assessing damage, e.g. delaminations, during service life. Standard multi-mode and single mode fibres with a typical length of a few hundreds of metres were embedded inside the walls of containers during the normal manufacturing process, and the measurements were carried out using an optical through-power technique and an OTDR. This largely empirical investigation revealed that the coating material and its thickness have an effect on loading sensitivity and on the applicability of the method for cure monitoring. The measurement data also indicated that the end-of-curing process and the location of external damage can be determined with a distributed optical fibre sensor and an OTDR. Several versions of a pulsed time-of-flight measurement system were developed for interrogating sensor arrays consisting of multiple long gauge-length sensors. The early versions based on commercial electronics were capable of producing relevant measurement data with a reasonable precision, but they suffered especially from poor spatial resolution, low sampling rate and long-term drift. The high precision TOF system developed in this thesis is capable of measuring time delays between a number of wideband reflectors, such as connectors or fibre Bragg gratings (FBG), along a fibre path with a precision of about 280 fs (rms-value) and a spatial resolution of about 3 ns (0.30 m) in a measurement time of 25 milliseconds. By using a fibre loop sensor with a reference fibre, a strain precision below 1 με and a measurement frequency of 4 Hz can be achieved. The system has proved comparable in performance to a commercial FBG interrogation system in monitoring the behaviour of a bridge deck, while the fact that it allows static and dynamic measurements with a number of long gauge-length sensors, also embedded in FRP composite material, makes this TOF device unique relative to other measurement systems.

Les travaux réalisés se situent dans le cadre de CSI en mode passif. Une méthode d’identification de défauts se basant sur les fonctions d’inter-corrélations a été proposée et a donné naissance à deux critères d’identifications. Le premier est un critère visuel, ce critère est basé sur la superposition des enveloppes des fonctions d’inter-corrélation obtenues par transformée de Hilbert pour deux configurations dont l’une est sans défaut et l’autre est avec défaut. Le deuxième critère est numérique, il s’agit de la moyenne des écarts entre deux enveloppes que l’on appelle CEI. Les performances de ces critères ont été testées premièrement sur une plaque en aluminium en conditions libres, en utilisant une source localisée en espace ayant une intensité non contrôlée. Les résultats de la première expérience ont montré certes la sensibilité de ces critères à l’apparition des défauts, mais également une forte sensibilité aux changements de la position de la source, c’est pour cette raison qu’une deuxième expérience utilisant une source localisée non localisée en espace à été effectuée. Les critères proposés ont d’abords été testé en utilisant un signal sinus mono fréquence comme source, et en utilisant un bruit blanc filtré comme source par la suite. Grâce aux critères proposés, le défaut est certes identifié, néanmoins, il reste à trouver un moyen pour le localiser et pour le caractériser. / The work presented is in the domain of SHM. An identification method based on the cross correlations functions between piezoelectric sensors was proposed and gave birth to two criterion of identification. The first is a visual criterion, it is based on the superposition of the envelopes of the cross correlation functions obtained by Hilbert transform for two configurations, the first is a defect free configuration of reference and the other is with defect.The second criterion is numerical; it is the mean of the differences between two envelopes. The performance of these criterions was tested first on an aluminum plate in free edges conditions, using a source located in space; the intensity of this source was not controlled. The results of the first experiment has certainly shown the sensitivity of these criterion to the appearance of defects despite the randomness of the source, but also highly sensitivity to changes in the position of the source was found. In the second experiment a source not localized in space was used, and the plate was in clamped edges conditions. The proposed criterions have been tested using a single frequency sine signal as a source first and using a white noise filtered signal secondly. With the proposed criterion, the defect was certainly identified; however, it remains to find a way to locate and to characterize the defect.

In this thesis, miniaturized wavelength interrogators based on planar lightwave circuits (PLCs) are investigated and developed for the optical fiber sensing applications in the aircraft structural health monitoring (SHM) and optofluidic analysis. Two interrogation systems based on an arrayed waveguide grating (AWG) and an Echelle diffractive grating (EDG) are developed and used to convert the optical sensing signals into strain, temperature, vibration, damage, and humidity information for the aircraft SHM. A fiber Bragg grating (FBG) sensing system using developed interrogators is then demonstrated in a field test for aircraft SHM applications. For optofluidic analysis, a PLCs based optofluidic device consisting of two on-chip lens sets is built to enhance the optical manipulation capability of particles. Then, a solution to a multi-functional Lab-on-a-Chip platform for optofluidic analysis is proposed, which integrates the developed particle maneuvering device, grating-structured sensors, and miniaturized interrogators.