Application of PZT and FBG impedance sensors for structural health monitoring of reinforced concrete beams strengthened with FRP composite materials

Esta Tesis tiene como objetivo principal el desarrollo de métodos de identificación del daño que sean robustos y fiables, enfocados a sistemas estructurales experimentales, fundamentalmente a las estructuras de hormigón armado reforzadas externamente con bandas fibras de polímeros reforzados (FRP). El modo de fallo de este tipo de sistema estructural es crítico, pues generalmente es debido a un despegue repentino y frágil de la banda del refuerzo FRP originado en grietas intermedias causadas por la flexión. La detección de este despegue en su fase inicial es fundamental para prevenir fallos futuros, que pueden ser catastróficos. Inicialmente, se lleva a cabo una revisión del método de la Impedancia Electro-Mecánica (EMI), de cara a exponer sus capacidades para la detección de daño. Una vez la tecnología apropiada es seleccionada, lo que incluye un analizador de impedancias así como novedosos sensores PZT para monitorización inteligente, se ha diseñado un procedimiento automático basado en los registros de impedancias de distintas estructuras de laboratorio. Basándonos en el hecho de que las mediciones de impedancias son posibles gracias a una colocación adecuada de una red de sensores PZT, la estimación de la presencia de daño se realiza analizando los resultados de distintos indicadores de daño obtenidos de la literatura. Para que este proceso sea automático y que no sean necesarios conocimientos previos sobre el método EMI para realizar un experimento, se ha diseñado e implementado un Interfaz Gráfico de Usuario, transformando la medición de impedancias en un proceso fácil e intuitivo. Se evalúa entonces el daño a través de los correspondientes índices de daño, intentando estimar no sólo su severidad, sino también su localización aproximada. El desarrollo de estos experimentos en cualquier estructura genera grandes cantidades de datos que han de ser procesados, y algunas veces los índices de daño no son suficientes para una evaluación completa de la integridad de una estructura. En la mayoría de los casos se pueden encontrar patrones de daño en los datos, pero no se tiene información a priori del estado de la estructura. En este punto, se ha hecho una importante investigación en técnicas de reconocimiento de patrones particularmente en aprendizaje no supervisado, encontrando aplicaciones interesantes en el campo de la medicina. De ahí surge una idea creativa e innovadora: detectar y seguir la evolución del daño en distintas estructuras como si se tratase de un cáncer propagándose por el cuerpo humano. En ese sentido, las lecturas de impedancias se emplean como información intrínseca de la salud de la propia estructura, de forma que se pueden aplicar las mismas técnicas que las empleadas en la investigación del cáncer. En este caso, se ha aplicado un algoritmo de clasificación jerárquica dado que ilustra además la clasificación de los datos de forma gráfica, incluyendo información cualitativa y cuantitativa sobre el daño. Se ha investigado la efectividad de este procedimiento a través de tres estructuras de laboratorio, como son una viga de aluminio, una unión atornillada de aluminio y un bloque de hormigón reforzado con FRP. La primera ayuda a mostrar la efectividad del método en sencillos escenarios de daño simple y múltiple, de forma que las conclusiones extraídas se aplican sobre los otros dos, diseñados para simular condiciones de despegue en distintas estructuras. Demostrada la efectividad del método de clasificación jerárquica de lecturas de impedancias, se aplica el procedimiento sobre las estructuras de hormigón armado reforzadas con bandas de FRP objeto de esta tesis, detectando y clasificando cada estado de daño. Finalmente, y como alternativa al anterior procedimiento, se propone un método para la monitorización continua de la interfase FRP-Hormigón, a través de una red de sensores FBG permanentemente instalados en dicha interfase. De esta forma, se obtienen medidas de deformación de la interfase en condiciones de carga continua, para ser implementadas en un modelo de optimización multiobjetivo, cuya solución se haya por medio de una expansión multiobjetivo del método Particle Swarm Optimization (PSO). La fiabilidad de este último método de detección se investiga a través de sendos ejemplos tanto numéricos como experimentales. ABSTRACT This thesis aims to develop robust and reliable damage identification methods focused on experimental structural systems, in particular Reinforced Concrete (RC) structures externally strengthened with Fiber Reinforced Polymers (FRP) strips. The failure mode of this type of structural system is critical, since it is usually due to sudden and brittle debonding of the FRP reinforcement originating from intermediate flexural cracks. Detection of the debonding in its initial stage is essential thus to prevent future failure, which might be catastrophic. Initially, a revision of the Electro-Mechanical Impedance (EMI) method is carried out, in order to expose its capabilities for local damage detection. Once the appropriate technology is selected, which includes impedance analyzer as well as novel PZT sensors for smart monitoring, an automated procedure has been design based on the impedance signatures of several lab-scale structures. On the basis that capturing impedance measurements is possible thanks to an adequately deployed PZT sensor network, the estimation of damage presence is done by analyzing the results of different damage indices obtained from the literature. In order to make this process automatic so that it is not necessary a priori knowledge of the EMI method to carry out an experimental test, a Graphical User Interface has been designed, turning the impedance measurements into an easy and intuitive procedure. Damage is then assessed through the analysis of the corresponding damage indices, trying to estimate not only the damage severity, but also its approximate location. The development of these tests on any kind of structure generates large amounts of data to be processed, and sometimes the information provided by damage indices is not enough to achieve a complete analysis of the structural health condition. In most of the cases, some damage patterns can be found in the data, but none a priori knowledge of the health condition is given for any structure. At this point, an important research on pattern recognition techniques has been carried out, particularly on unsupervised learning techniques, finding interesting applications in the medicine field. From this investigation, a creative and innovative idea arose: to detect and track the evolution of damage in different structures, as if it were a cancer propagating through a human body. In that sense, the impedance signatures are used to give intrinsic information of the health condition of the structure, so that the same clustering algorithms applied in the cancer research can be applied to the problem addressed in this dissertation. Hierarchical clustering is then applied since it also provides a graphical display of the clustered data, including quantitative and qualitative information about damage. The performance of this approach is firstly investigated using three lab-scale structures, such as a simple aluminium beam, a bolt-jointed aluminium beam and an FRP-strengthened concrete specimen. The first one shows the performance of the method on simple single and multiple damage scenarios, so that the first conclusions can be extracted and applied to the other two experimental tests, which are designed to simulate a debonding condition on different structures. Once the performance of the impedance-based hierarchical clustering method is proven to be successful, it is then applied to the structural system studied in this dissertation, the RC structures externally strengthened with FRP strips, where the debonding failure in the interface between the FRP and the concrete is successfully detected and classified, proving thus the feasibility of this method. Finally, as an alternative to the previous approach, a continuous monitoring procedure of the FRP-Concrete interface is proposed, based on an FBGsensors Network permanently deployed within that interface. In this way, strain measurements can be obtained under controlled loading conditions, and then they are used in order to implement a multi-objective model updating method solved by a multi-objective expansion of the Particle Swarm Optimization (PSO) method. The feasibility of this last proposal is investigated and successfully proven on both numerical and experimental RC beams strengthened with FRP.

Self-adaptive strategy based on fuzzy control systems for improving performance in wireless sensors networks

The solutions to cope with new challenges that societies have to face nowadays involve providing smarter daily systems. To achieve this, technology has to evolve and leverage physical systems automatic interactions, with less human intervention. Technological paradigms like Internet of Things (IoT) and Cyber-Physical Systems (CPS) are providing reference models, architectures, approaches and tools that are to support cross-domain solutions. Thus, CPS based solutions will be applied in different application domains like e-Health, Smart Grid, Smart Transportation and so on, to assure the expected response from a complex system that relies on the smooth interaction and cooperation of diverse networked physical systems. The Wireless Sensors Networks (WSN) are a well-known wireless technology that are part of large CPS. The WSN aims at monitoring a physical system, object, (e.g., the environmental condition of a cargo container), and relaying data to the targeted processing element. The WSN communication reliability, as well as a restrained energy consumption, are expected features in a WSN. This paper shows the results obtained in a real WSN deployment, based on SunSPOT nodes, which carries out a fuzzy based control strategy to improve energy consumption while keeping communication reliability and computational resources usage among boundaries.

Calibración de sensores de fuerza bajo estímulos sinusoidales: contribuciones a su caracterización

El presente trabajo tiene como objetivo el desarrollo de un patrón primario para la calibración de sensores de fuerza bajo excitaciones sinusoidales. Con consecuencia de dicho desarrollo se establecerá un método de calibración de sensores de fuerza en condiciones dinámicas que permitirá la caracterización de estos sensores en dichas condiciones y determinar la incertidumbre asociada. Este patrón se basa en la definición directa de fuerza como masa por aceleración. Para ello se carga el sensor con distintas cargas calibradas y se somete a distintas aceleraciones mediante un excitador de vibraciones. Dichas aceleraciones se generan para frecuencias desde 5 Hz a 2400 Hz. La aceleración se mide mediante un vibrómetro láser con trazabilidad a la unidad de longitud (longitud de onda del láser). Al ser una medición completamente dinámica se necesita un sistema de adquisición de datos multicanal para la toma de datos en tiempo real. Este sistema adquiere las señales eléctricas provenientes del vibrómetro láser, del sensor a caracterizar y del acelerómetro para mediciones auxiliares. Se ha dispuesto de cuatro sensores de fuerza para realizar ensayos, un sensor piezoeléctrico y tres sensores resistivos. En este trabajo se han estudiado los factores de influencia y se ha implementado un método de calibración para minimizar los mismos, así como también se han establecido las correcciones a realizar. Para la caracterización dinámica del sensor se ha partido de un modelo de oscilador armónico amortiguado forzado, se ha establecido la metodología para la determinación de sus parámetros de caracterización y se ha estudiado su validez. También se ha realizado una comparación entre los resultados obtenidos para condiciones estáticas y dinámicas. ABSTRACT The aim in the current work is the development of a primary standard for force sensors calibration under sinusoidal excitations. As consequence of this development a method for force sensors calibration under dynamic conditions will be established that will allow these sensors characterization for such conditions and the determination of their associated uncertainty. This standard is based on the direct definition of force as mass multiplied by acceleration. To do so, the sensor is loaded with different calibrated loads and is maintained under different accelerations by means of a vibration shaker. These accelerations are generated with frequencies from 5 Hz up to 2400 Hz. The acceleration is measured by means of a laser vibrometer with traceability to the unit of length (laser wavelength). As the measurement is totally dynamic a multiple channel data acquisition system is required for data acquisition in real time. This system acquires the electrical signals outputs coming from the laser vibrometer, the sensor to be characterised and two accelerometers for additional measurements. Four force sensors, one piezoelectric sensor and three resistive sensors, have been available to perform the tests. During this work the influence factors have been studied and a calibration method to minimise these factors have been implemented as well as the corrections to be performed have been established. As the starting point for the sensor dynamic characterization, a model for a forced damped harmonic oscillator has been used, a method for the characterizing parameters determination has been established and its validity has been studied. A comparison between results for static and dynamic conditions has been performed as well.

Multi-distributed wireless sensors for monitoring a long distance transport in a reefer container

The study of the temperature gradients in cold stores and containers is a critical issue in the food industry for the quality assurance of products during transport and for minimising losses. This work presents an analysis of the temperatures during the refrigerated transport of 4,320 kg of blueberries in a reefer (set point temperature at ?1ºC) on a container ship from Montevideo (Uruguay) to Verona (Italy). The monitoring was performed by using semi-passive RFID loggers (TurboTag cards). The objective was to carry out a multi-distributed supervision using low-cost, wireless and autonomous sensors for the characterisation of the distribution and spatial gradients of temperatures during a long distance transport. Data analysis shows spatial (phase space) and temporal sequencing diagrams and reveals a significant heterogeneity of temperature at different locations in the container, which highlights the ineffectiveness of a temperature control system based on a single sensor, as is usually done.

Lock-in amplifiers for AMR sensors

Anisotropic magnetoresistive (AMR) magnetic sensors are often chosen as the magnetic transducer for magnetic field sensing in applications with low to moderate magnetic field resolution because of the relative low mass of the sensor and their ease of use. They measure magnetic fields in the order of the Earth magnetic field (with typical sensitivities of 1‰/G or 10−2‰/μT), have typical minimum detectable fields in order of nT and even 0.1 nT but they are seriously limited by the thermal drifts due to the variation of the resistivity with temperature (∼2.5‰/°C) and the variation of the magnetoresistive effect with temperature (which affects both the sensitivity of the sensors: ∼2.7‰/°C, and the offset: ±0.5‰/°C). Therefore, for lower magnetic fields, fluxgate vector sensors are generally preferred. In the present work these limitations of AMR sensors are outlined and studied. Three methods based on lock-in amplifiers are proposed as low noise techniques. Their performance has been simulated, experimentally tested and comparatively discussed. The developed model has been also used to derive a technique for temperature compensation of AMR response. The final goal to implement these techniques in a space qualified applied specific integrated circuit (ASIC) for Mars in situ exploration with compact miniaturized magnetometers.

Resonadores piezoeléctricos de cizalladura: estudio de la formación de biofilms y caracterización de fluidos magneto‐reológicos

La presente tesis revisa y analiza algunos aspectos fundamentales relativos al comportamiento de los sensores basados en resonadores piezoeléctricos TSM (Thickness Shear Mode), así como la aplicación de los mismos al estudio y caracterización de dos medios viscoelásticos de gran interés: los fluidos magnetoreológicos y los biofilms microbianos. El funcionamiento de estos sensores está basado en la medida de sus propiedades resonantes, las cuales varían al entrar en contacto con el material que se quiere analizar. Se ha realizado un análisis multifrecuencial, trabajando en varios modos de resonancia del transductor, en algunas aplicaciones incluso de forma simultánea (excitación pulsada). Se han revisado fenómenos como la presencia de microcontactos en la superficie del sensor y la resonancia de capas viscoelásticas de espesor finito, que pueden afectar a los sensores de cuarzo de manera contraria a lo que predice la teoría convencional (Sauerbrey y Kanazawa), pudiéndonos llevar a incrementos positivos de la frecuencia de resonancia. Además, se ha estudiado el efecto de una deposición no uniforme sobre el resonador piezoeléctrico. Para ello se han medido deposiciones de poliuretano, modelándose la respuesta del resonador con estas deposiciones mediante FEM. El modelo numérico permite estudiar el comportamiento del resonador al modificar distintas variables geométricas (espesor, superficie, no uniformidad y zona de deposición) de la capa depositada. Se ha demostrado que para espesores de entre un cuarto y media longitud de onda aproximadamente, una capa viscoelástica no uniforme sobre la superficie del sensor, amplifica el incremento positivo del desplazamiento de la frecuencia de resonancia en relación con una capa uniforme. Se ha analizado también el patrón geométrico de la sensibilidad del sensor, siendo también no uniforme sobre su superficie. Se han aplicado sensores TSM para estudiar los cambios viscoelásticos que se producen en varios fluidos magneto-reológicos (FMR) al aplicarles distintos esfuerzos de cizalla controlados por un reómetro. Se ha podido ver que existe una relación directa entre diversos parámetros reológicos obtenidos con el reómetro (fuerza normal, G’, G’’, velocidad de deformación, esfuerzo de cizalla…) y los parámetros acústicos, caracterizándose los FMR tanto en ausencia de campo magnético, como con campo magnético aplicado a distintas intensidades. Se han estudiado las ventajas que aporta esta técnica de medida sobre la técnica basada en un reómetro comercial, destacando que se consigue caracterizar con mayor detalle algunos aspectos relevantes del fluido como son la deposición de partículas (estabilidad del fluido), el proceso de ruptura de las estructuras formadas en los FMR tanto en presencia como en ausencia de campo magnético y la rigidez de los microcontactos que aparecen entre partículas y superficies. También se han utilizado sensores de cuarzo para monitorear en tiempo real la formación de biofilms de Staphylococcus epidermidis y Eschericia coli sobre los propios resonadores de cristal de cuarzo sin ningún tipo de recubrimiento, realizándose ensayos con cepas que presentan distinta capacidad de producir biofilm. Se mostró que, una vez que se ha producido una primera adhesión homogénea de las bacterias al sustrato, podemos considerar el biofilm como una capa semi-infinita, de la cual el sensor de cuarzo refleja las propiedades viscoelásticas de la región inmediatamente contigua al resonador, no siendo sensible a lo que sucede en estratos superiores del biofilm. Los experimentos han permitido caracterizar el módulo de rigidez complejo de los biofilms a varias frecuencias, mostrándose que el parámetro característico que indica la adhesión de un biofilm tanto en el caso de S. epidermidis como de E. coli, es el incremento de G’ (relacionado con la elasticidad o rigidez de la capa), el cual viene ligado a un incremento de la frecuencia de resonancia del sensor. ABSTRACT This thesis reviews and analyzes some key aspects of the behavior of sensors based on piezoelectric resonators TSM (Thickness Shear Mode) and their applications to the study and characterization in two viscoelastic media of great interest: magnetorheological fluids and microbial biofilms. The operation of these sensors is based on the analysis of their resonant properties that vary in contact with the material to be analyzed. We have made a multi-frequency analysis, working in several modes of resonance of the transducer, in some applications even simultaneously (by impulse excitation). We reviewed some phenomena as the presence of micro-contacts on the sensor surface and the resonance of viscoelastic layers of finite thickness, which can affect quartz sensors contrary to the conventional theory predictions (Sauerbrey and Kanazawa), leading to positive resonant frequency shifts. In addition, we studied the effect of non-uniform deposition on the piezoelectric resonator. Polyurethane stools have been measured, being the resonator response to these depositions modeled by FEM. The numerical model allows studying the behavior of the resonator when different geometric variables (thickness, surface non-uniformity and deposition zone) of the deposited layer are modified. It has been shown that for thicknesses between a quarter and a half of a wavelength approximately, non-uniform deposits on the sensor surface amplify the positive increase of the resonance frequency displacement compared to a uniform layer. The geometric pattern of the sensor sensitivity was also analyzed, being also non-uniform over its surface. TSM sensors have been applied to study the viscoelastic changes occurring in various magneto-rheological fluids (FMR) when subjected to different controlled shear stresses driven by a rheometer. It has been seen that there is a direct relationship between various rheological parameters obtained with the rheometer (normal force, G', G'', stress, shear rate ...) and the acoustic parameters, being the FMR characterized both in the absence of magnetic field, and when the magnetic field was applied at different intensities. We have studied the advantages of this technique over the characterization methods based on commercial rheometers, noting that TSM sensors are more sensitive to some relevant aspects of the fluid as the deposition of particles (fluid stability), the breaking process of the structures formed in the FMR both in the presence and absence of magnetic field, and the rigidity of the micro-contacts appearing between particles and surfaces. TSM sensors have also been used to monitor in real time the formation of biofilms of Staphylococcus epidermidis and Escherichia coli on the quartz crystal resonators themselves without any coating, performing tests with strains having different ability to produce biofilm. It was shown that, once a first homogeneous adhesion of bacteria was produced on the substrate, the biofilm can be considered as a semi-infinite layer and the quartz sensor reflects only the viscoelastic properties of the region immediately adjacent to the resonator, not being sensitive to what is happening in upper layers of the biofilm. The experiments allow the evaluation of the biofilm complex stiffness module at various frequencies, showing that the characteristic parameter that indicates the adhesion of a biofilm for the case of both S. epidermidis and E. coli, is an increased G' (related to the elasticity or stiffness of the layer), which is linked to an increase in the resonance frequency of the sensor.

On the Velocity and Acceleration Estimation from Discrete Time-Position Sensors

In this work is addressed the topic of estimation of velocity and acceleration from digital position data. It is presented a review of several classic methods and implemented with real position data from a low cost digital sensor of a hydraulic linear actuator. The results are analyzed and compared. It is shown that static methods have a limited bandwidth application, and that the performance of some methods may be enhanced by adapting its parameters according to the current state.

Self-Learning Embedded System for Object Identification in Intelligent Infrastructure Sensors

The emergence of new horizons in the field of travel assistant management leads to the development of cutting-edge systems focused on improving the existing ones. Moreover, new opportunities are being also presented since systems trend to be more reliable and autonomous. In this paper, a self-learning embedded system for object identification based on adaptive-cooperative dynamic approaches is presented for intelligent sensor’s infrastructures. The proposed system is able to detect and identify moving objects using a dynamic decision tree. Consequently, it combines machine learning algorithms and cooperative strategies in order to make the system more adaptive to changing environments. Therefore, the proposed system may be very useful for many applications like shadow tolls since several types of vehicles may be distinguished, parking optimization systems, improved traffic conditions systems, etc.