Using aircraft as wind sensors for estimating accurate wind fields for air traffic management applications

A study which examines the use of aircraft as wind sensors in a terminal area for real-time wind estimation in order to improve aircraft trajectory prediction is presented in this paper. We describe not only different sources in the aircraft systems that provide the variables needed to derivate the wind velocity but the capabilities which allow us to present this information for ATM Applications. Based on wind speed samples from aircraft landing at Madrid-Barajas airport, a real-time wind field will be estimated using a data processing approach through a minimum variance method. Finally the accuracy of this procedure will be evaluated for this information to be useful to Air Traffic Control.

Debonding identification in FRP-plated RC structures using PZT sensors

The application of the Electro-Mechanical Impedance (EMI) method for damage detection in Structural Health Monitoring has noticeable increased in recent years. EMI method utilizes piezoelectric transducers for directly measuring the mechanical properties of the host structure, obtaining the so called impedance measurement, highly influenced by the variations of dynamic parameters of the structure. These measurements usually contain a large number of frequency points, as well as a high number of dimensions, since each frequency range swept can be considered as an independent variable. That makes this kind of data hard to handle, increasing the computational costs and being substantially time-consuming. In that sense, the Principal Component Analysis (PCA)-based data compression has been employed in this work, in order to enhance the analysis capability of the raw data. Furthermore, a Support Vector Machine (SVM), which has been widespread used in machine learning and pattern recognition fields, has been applied in this study in order to model any possible existing pattern in the PCAcompress data, using for that just the first two Principal Components. Different known non-damaged and damaged measurements of an experimental tested beam were used as training input data for the SVM algorithm, using as test input data the same amount of cases measured in beams with unknown structural health conditions. Thus, the purpose of this work is to demonstrate how, with a few impedance measurements of a beam as raw data, its healthy status can be determined based on pattern recognition procedures.

Methodology based on FBG sensors for monitoring of FRP-strengthened beams

Advanced composite materials are increasingly used in the strengthening of reinforced concrete (RC) structures. The use of externally bonded strips made of fibre-reinforced plastics (FRP) as strengthening method has gained widespread acceptance in recent years since it has many advantages over the traditional techniques. However, unfortunately, this strengthening method is often associated with a brittle and sudden failure caused by some form of FRP bond failure, originated at the termination of the FRP material or at intermediate areas in the vicinity of flexural cracks in the RC beam. Up to date, little effort in the early prediction of the debonding in its initial instants even though this effect is not noticeable by simple visual observation. An early detection of this phenomenon might help in taking actions to prevent future catastrophes. Fibre-optic Bragg grating (FBG) sensors are able to measure strains locally with high resolution and accuracy. Furthermore, as their physical size is extremely small compared with other strain measuring components, it enables to be embedded at the concrete-FRP interface for determining the strain distribution without influencing the mechanical properties of the host materials. This paper shows the development of a debonding identification methodology based on strains experimentally measured. For, it a simplified model is implemented to simulate the behaviour of FRP-strengthened reinforced concrete beams. This model is taken as a basis to. develop an model updating procedure able to detect minor debonding at the concrete-FRP interface from experimental strains obtained by using FBG sensors embedded at the interface

Ground and airborne level optical sensors: is it possible to estimate maize crop N status?

Adjusting N fertilizer application to crop requirements is a key issue to improve fertilizer efficiency, reducing unnecessary input costs to farmers and N environmental impact. Among the multiple soil and crop tests developed, optical sensors that detect crop N nutritional status may have a large potential to adjust N fertilizer recommendation (Samborski et al. 2009). Optical readings are rapid to take and non-destructive, they can be efficiently processed and combined to obtain indexes or indicators of crop status. However, other physiological stress conditions may interfere with the readings and detection of the best crop nutritional status indicators is not always and easy task. Comparison of different equipments and technologies might help to identify strengths and weakness of the application of optical sensors for N fertilizer recommendation. The aim of this study was to evaluate the potential of various ground-level optical sensors and narrow-band indices obtained from airborne hyperspectral images as tools for maize N fertilizer recommendations. Specific objectives were i) to determine which indices could detect differences in maize plants treated with different N fertilizer rates, and ii) to evaluate its ability to identify N-responsive from non-responsive sites.

Caracterización Avanzada de Tanques de Fermentación de Café mediante una Red Multidistribuida de Sensores RFID

La fermentación de las bayas de café se considera una et apa crítica en el procesado del café debido a su impacto en la calidad final del producto. La temperatura es una de las principales variables de control que puede ser utilizada para predecir el final del proceso, teniendo en cuenta que varios autores indican que el control de esta etapa es fundamental para evitar la mala calidad de la be bida final. En la práctica, la fermentación es el paso menos controlado del proceso, haciendo que los beneficiaderos operen lejos de sus condiciones óptimas en términos de costes de operación (es decir, elevados consumos de energía y agua) y de calidad del producto final. El objetivo de este trabajo es caracterizar los gradientes de temperatura que se dan en los tanques de fermentación mediante una red multi-distribuida de sensores autónomos, inalámbricos y de bajo coste (registradores de temperatura del tipo RFID, identificadores de radiofrecuencia semipasivos modelo TurboTag®).Para ello se utilizan dos metodologías: la interpolación espacial en coordenadas polares y los diagramas de espacio de fase. Se supervisaron dos fermentaciones reales de café, en El Cauca (Colombia), mediante sensores sumergidos directamente en la masa en fermentación. Los fermentadores eran tanques de plástico cubiertos, uno de ellos colocado en el interior de un almacén, permaneciendo el otro a la intemperie. El rango de variación máximo de temperatura en los tanques fue de 4,5ºC. La interpolación espacial mostró, incluso en el fermentador bajo las condiciones menos desfavorables en el interior del almacén, un gradiente radial de temperatura instantáneo de 0,1 °C/cm desde el centro hasta el perímetro del tanque y un gradiente vertical de temperatura de 0,25 °C/cm para sensores con coordenadas polares iguales. La combinación de ambas metodologías permitió la identificación consistente de los puntos calientes y fríos de ambas fermentaciones.

Caracterización Avanzada de Tanques de Fermentación de Café medinate una Red Multidistribuida de Sensores RFID

Las hortalizas mínimamente procesadas (MP) son productos frescos, higienizados, que sufren alteraciones físicas durante el proceso de elaboración que afectan a su metabolismo, determinando incrementos en la tasa respiratoria y producción de etileno. Los daños que se originan por las operaciones físicas, vuelven a estos productos más susceptibles a la colonización de microorganismos, inducen procesos de cicatrización de heridas y afectan su calidad organoléptica y funcional. Por ello en estos productos es especialmente crítico el aseguramiento de las condiciones de refrigeración desde el productor hasta el consumidor. En este estudio se presenta el análisis de las temperaturas registradas en Santiago (Chile) durante la cadena de producción y distribución de lechugas baby leaf MP tipo Salanova®, monitorizadas mediante sensores de temperatura y humedad relativa (I-Buttons®) y tarjetas RFID con sensor de temperatura (TurboTag®), colocados en el interior de las bolsas de lechuga y en el exterior de las cajas de agrupación. El objetivo del presente trabajo es generar información sobre el historial térmico de estos productos desde la huerta a la nevera del consumidor, así como optimizar los protocolos de colocación de dispositivos y sistematizar procedimientos de análisis de datos espacio-temporales. Con los datos registrados, se simuló la cadena de producción, distribución y venta, realizando un seguimiento de la calidad comercial del producto, evaluándose la tasa respiratoria y las características sensoriales sin degustación. Se observó que no solo se producen saltos térmicos discretos, sino que las lechugas estuvieron durante gran parte de su vida útil en condiciones sub-óptimas de temperatura, comprometiéndose su calidad sensorial.

Advanced background modeling with RGB-D sensors through classifiers combination and inter-frame foreground prediction

An innovative background modeling technique that is able to accurately segment foreground regions in RGB-D imagery (RGB plus depth) has been presented in this paper. The technique is based on a Bayesian framework that efficiently fuses different sources of information to segment the foreground. In particular, the final segmentation is obtained by considering a prediction of the foreground regions, carried out by a novel Bayesian Network with a depth-based dynamic model, and, by considering two independent depth and color-based mixture of Gaussians background models. The efficient Bayesian combination of all these data reduces the noise and uncertainties introduced by the color and depth features and the corresponding models. As a result, more compact segmentations, and refined foreground object silhouettes are obtained. Experimental results with different databases suggest that the proposed technique outperforms existing state-of-the-art algorithms.

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.

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.

Supervisión multidistribuida para el control de procesos de conservación de productos agroalimentarios: optimización de calidad del producto

La presente Tesis está orientada al análisis de la supervisión multidistribuida de tres procesos agroalimentarios: el secado solar, el transporte refrigerado y la fermentación de café, a través de la información obtenida de diferentes dispositivos de adquisición de datos, que incorporan sensores, así como el desarrollo de metodologías de análisis de series temporales, modelos y herramientas de control de procesos para la ayuda a la toma de decisiones en las operaciones de estos entornos. En esta tesis se han utilizado: tarjetas RFID (TemTrip®) con sistema de comunicación por radiofrecuencia y sensor de temperatura; el registrador (i-Button®), con sensor integrado de temperatura y humedad relativa y un tercer prototipo empresarial, módulo de comunicación inalámbrico Nlaza, que integra un sensor de temperatura y humedad relativa Sensirion®. Estos dispositivos se han empleado en la conformación de redes multidistribuidas de sensores para la supervisión de: A) Transportes de producto hortofrutícola realizados en condiciones comerciales reales, que son: dos transportes terrestre de producto de IV gama desde Murcia a Madrid; transporte multimodal (barco-barco) de limones desde Montevideo (Uruguay) a Cartagena (España) y transporte multimodal (barco-camión) desde Montevideo (Uruguay) a Verona (Italia). B) dos fermentaciones de café realizadas en Popayán (Colombia) en un beneficiadero. Estas redes han permitido registrar la dinámica espacio-temporal de temperaturas y humedad relativa de los procesos estudiados. En estos procesos de transporte refrigerado y fermentación la aplicación de herramientas de visualización de datos y análisis de conglomerados, han permitido identificar grupos de sensores que presentan patrones análogos de sus series temporales, caracterizando así zonas con dinámicas similares y significativamente diferentes del resto y permitiendo definir redes de sensores de menor densidad cubriendo las diferentes zonas identificadas. Las metodologías de análisis complejo de las series espacio-temporales (modelos psicrométricos, espacio de fases bidimensional e interpolaciones espaciales) permitieron la cuantificación de la variabilidad del proceso supervisado tanto desde el punto de vista dinámico como espacial así como la identificación de eventos. Constituyendo así herramientas adicionales de ayuda a la toma de decisiones en el control de los procesos. Siendo especialmente novedosa la aplicación de la representación bidimensional de los espacios de fases en el estudio de las series espacio-temporales de variables ambientales en aplicaciones agroalimentarias, aproximación que no se había realizado hasta el momento. En esta tesis también se ha querido mostrar el potencial de un sistema de control basado en el conocimiento experto como es el sistema de lógica difusa. Se han desarrollado en primer lugar, los modelos de estimación del contenido en humedad y las reglas semánticas que dirigen el proceso de control, el mejor modelo se ha seleccionado mediante un ensayo de secado realizado sobre bolas de hidrogel como modelo alimentario y finalmente el modelo se ha validado mediante un ensayo en el que se deshidrataban láminas de zanahoria. Los resultados sugirieron que el sistema de control desarrollado, es capaz de hacer frente a dificultades como las variaciones de temperatura día y noche, consiguiendo un producto con buenas características de calidad comparables a las conseguidas sin aplicar ningún control sobre la operación y disminuyendo así el consumo energético en un 98% con respecto al mismo proceso sin control. La instrumentación y las metodologías de análisis de datos implementadas en esta Tesis se han mostrado suficientemente versátiles y transversales para ser aplicadas a diversos procesos agroalimentarios en los que la temperatura y la humedad relativa sean criterios de control en dichos procesos, teniendo una aplicabilidad directa en el sector industrial ABSTRACT This thesis is focused on the analysis of multi-distributed supervision of three agri-food processes: solar drying, refrigerated transport and coffee fermentation, through the information obtained from different data acquisition devices with incorporated sensors, as well as the development of methodologies for analyzing temporary series, models and tools to control processes in order to help in the decision making in the operations within these environments. For this thesis the following has been used: RFID tags (TemTrip®) with a Radiofrequency ID communication system and a temperature sensor; the recorder (i-Button®), with an integrated temperature and relative humidity and a third corporate prototype, a wireless communication module Nlaza, which has an integrated temperature and relative humidity sensor, Sensirion®. These devices have been used in creating three multi-distributed networks of sensors for monitoring: A) Transport of fruits and vegetables made in real commercial conditions, which are: two land trips of IV range products from Murcia to Madrid; multimodal transport (ship - ship) of lemons from Montevideo (Uruguay) to Cartagena (Spain) and multimodal transport (ship - truck) from Montevideo (Uruguay) to Verona (Italy). B) Two coffee fermentations made in Popayan (Colombia) in a coffee processing plant. These networks have allowed recording the time space dynamics of temperatures and relative humidity of the processed under study. Within these refrigerated transport and fermentation processes, the application of data display and cluster analysis tools have allowed identifying sensor groups showing analogical patterns of their temporary series; thus, featuring areas with similar and significantly different dynamics from the others and enabling the definition of lower density sensor networks covering the different identified areas. The complex analysis methodologies of the time space series (psychrometric models, bi-dimensional phase space and spatial interpolation) allowed quantifying the process variability of the supervised process both from the dynamic and spatial points of view; as well as the identification of events. Thus, building additional tools to aid decision-making on process control brought the innovative application of the bi-dimensional representation of phase spaces in the study of time-space series of environmental variables in agri-food applications, an approach that had not been taken before. This thesis also wanted to show the potential of a control system based on specialized knowledge such as the fuzzy logic system. Firstly, moisture content estimation models and semantic rules directing the control process have been developed, the best model has been selected by an drying assay performed on hydrogel beads as food model; and finally the model has been validated through an assay in which carrot sheets were dehydrated. The results suggested that the control system developed is able to cope with difficulties such as changes in temperature daytime and nighttime, getting a product with good quality features comparable to those features achieved without applying any control over the operation and thus decreasing consumption energy by 98% compared to the same uncontrolled process. Instrumentation and data analysis methodologies implemented in this thesis have proved sufficiently versatile and cross-cutting to apply to several agri-food processes in which the temperature and relative humidity are the control criteria in those processes, having a direct effect on the industry sector.

Design, Technology and Characterization of Micromechanised Sensors and Actuators for Harsh Environments

Los sistemas micro electro mecánicos (MEMS) han demostrado ser una exitosa familia de dispositivos que pueden usarse como plataforma para el desarrollo de dispositivos con aplicaciones en óptica, comunicaciones, procesado de señal y sensorización. Los dispositivos MEMS estándar suelen estar fabricados usando tecnología de silicio. Sin embargo, el rendimiento de estos MEMS se puede mejorar si se usan otros materiales. Por ejemplo, el diamante nanocristalino (NCD) ofrece unas excelentes propiedades mecánicas, transparencia y una superficie fácil de funcionalizar. Por otro lado, el sistema de materiales (In; Ga; Al)N, los materiales IIIN, se pueden usar para producir estructuras monocristalinas con alta sensibilidad mecánica y química. Además, el AlN se puede depositar por pulverización catódica reactiva sobre varios substratos, incluyendo NCD, para formar capas policristalinas orientadas con alta respuesta piezoeléctrica. Adicionalmente, tanto el NCD como los materiales III-N muestran una gran estabilidad térmica y química, lo que los hace una elección idónea para desarrollar dispositivos para aplicaciones para alta temperatura, ambientes agresivos e incluso para aplicaciones biocompatibles. En esta tesis se han usado estos materiales para el diseño y medición de demostradores tecnológicos. Se han perseguido tres objetivos principales: _ Desarrollo de unos procesos de fabricación apropiados. _ Medición de las propiedades mecánicas de los materiales y de los factores que limitan el rendimiento de los dispositivos. _ Usar los datos medidos para desarrollar dispositivos demostradores complejos. En la primera parte de esta tesis se han estudiado varias técnicas de fabricación. La estabilidad de estos materiales impide el ataque y dificulta la producción de estructuras suspendidas. Los primeros capítulos de esta disertación se dedican al desarrollo de unos procesos de transferencia de patrones por ataque seco y a la optimización del ataque húmedo sacrificial de varios substratos propuestos. Los resultados de los procedimientos de ataque se presentan y se describe la optimización de las técnicas para la fabricación de estructuras suspendidas de NCD y materiales III-N. En un capítulo posterior se estudia el crecimiento de AlN por pulverización catódica. Como se ha calculado en esta disertación para obtener una actuación eficiente de MEMS, las capas de AlN han de ser finas, típicamente d < 200 nm, lo que supone serias dificultades para la obtención de capas orientadas con respuesta piezoeléctrica. Las condiciones de depósito se han mapeado para identificar las fronteras que proporcionan el crecimiento de material orientado desde los primeros pasos del proceso. Además, durante la optimización de los procesos de ataque se estudió un procedimiento para fabricar películas de GaN nanoporoso. Estas capas porosas pueden servir como capas sacrificiales para la fabricación de estructuras suspendidas de GaN con baja tensión residual o como capas para mejorar la funcionalización superficial de sensores químicos o biológicos. El proceso de inducción de poros se discutirá y también se presentarán experimentos de ataque y funcionalización. En segundo lugar, se han determinado las propiedades mecánicas del NCD y de los materiales III-N. Se han fabricado varias estructuras suspendidas para la medición del módulo de Young y de la tensión residual. Además, las estructuras de NCD se midieron en resonancia para calcular el rendimiento de los dispositivos en términos de frecuencia y factor de calidad. Se identificaron los factores intrínsecos y extrínsecos que limitan ambas figuras de mérito y se han desarrollado modelos para considerar estas imperfecciones en las etapas de diseño de los dispositivos. Por otra parte, los materiales III-N normalmente presentan grandes gradientes de deformación residual que causan la deformación de las estructuras al ser liberadas. Se han medido y modelado estos efectos para los tres materiales binarios del sistema para proporcionar puntos de interpolación que permitan predecir las características de las aleaciones del sistema III-N. Por último, los datos recabados se han usado para desarrollar modelos analíticos y numéricos para el diseño de varios dispositivos. Se han estudiado las propiedades de transducción y se proporcionan topologías optimizadas. En el último capítulo de esta disertación se presentan diseños optimizados de los siguientes dispositivos: _ Traviesas y voladizos de AlN=NCD con actuación piezoeléctrica aplicados a nanoconmutadores de RF para señales de alta potencia. _ Membranas circulares de AlN=NCD con actuación piezoeléctrica aplicadas a lentes sintonizables. _ Filtros ópticos Fabry-Pérot basados en cavidades aéreas y membranas de GaN actuadas electrostáticamente. En resumen, se han desarrollado unos nuevos procedimientos optimizados para la fabricación de estructuras de NCD y materiales III-N. Estas técnicas se han usado para producir estructuras que llevaron a la determinación de las principales propiedades mecánicas y de los parámetros de los dispositivos necesarios para el diseño de MEMS. Finalmente, los datos obtenidos se han usado para el diseño optimizado de varios dispositivos demostradores. ABSTRACT Micro Electro Mechanical Systems (MEMS) have proven to be a successful family of devices that can be used as a platform for the development of devices with applications in optics, communications, signal processing and sensorics. Standard MEMS devices are usually fabricated using silicon based materials. However, the performance of these MEMS can be improved if other material systems are used. For instance, nanocrystalline diamond (NCD) offers excellent mechanical properties, optical transparency and ease of surface functionalization. On the other hand, the (In; Ga; Al)N material system, the III-N materials, can be used to produce single crystal structures with high mechanical and chemical sensitivity. Also, AlN can be deposited by reactive sputtering on various substrates, including NCD, to form oriented polycrystalline layers with high piezoelectric response. In addition, both NCD and III-N materials exhibit high thermal and chemical stability, which makes these material the perfect choice for the development of devices for high temperatures, harsh environments and even biocompatible applications. In this thesis these materials have been used for the design and measurement of technological demonstrators. Three main objectives have been pursued: _ Development of suitable fabrication processes. _ Measurement of the material mechanical properties and device performance limiting factors. _ Use the gathered data to design complex demonstrator devices. In a first part of the thesis several fabrication processes have been addressed. The stability of these materials hinders the etching of the layers and hampers the production of free standing structures. The first chapters of this dissertation are devoted to the development of a dry patterning etching process and to sacrificial etching optimization of several proposed substrates. The results of the etching processes are presented and the optimization of the technique for the manufacturing of NCD and III-N free standing structures is described. In a later chapter, sputtering growth of thin AlN layers is studied. As calculated in this dissertation, for efficient MEMS piezoelectric actuation the AlN layers have to be very thin, typically d < 200 nm, which poses serious difficulties to the production of c-axis oriented material with piezoelectric response. The deposition conditions have been mapped in order to identify the boundaries that give rise to the growth of c-axis oriented material from the first deposition stages. Additionally, during the etching optimization a procedure for fabricating nanoporous GaN layers was also studied. Such porous layers can serve as a sacrificial layer for the release of low stressed GaN devices or as a functionalization enhancement layer for chemical and biological sensors. The pore induction process will be discussed and etching and functionalization trials are presented. Secondly, the mechanical properties of NCD and III-N materials have been determined. Several free standing structures were fabricated for the measurement of the material Young’s modulus and residual stress. In addition, NCD structures were measured under resonance in order to calculate the device performance in terms of frequency and quality factor. Intrinsic and extrinsic limiting factors for both figures were identified and models have been developed in order to take into account these imperfections in the device design stages. On the other hand, III-N materials usually present large strain gradients that lead to device deformation after release. These effects have been measured and modeled for the three binary materials of the system in order to provide the interpolation points for predicting the behavior of the III-N alloys. Finally, the gathered data has been used for developing analytic and numeric models for the design of various devices. The transduction properties are studied and optimized topologies are provided. Optimized design of the following devices is presented at the last chapter of this dissertation: _ AlN=NCD piezoelectrically actuated beams applied to RF nanoswitches for large power signals. _ AlN=NCD piezoelectrically actuated circular membranes applied to tunable lenses. _ GaN based air gap tunable optical Fabry-Pérot filters with electrostatic actuation. On the whole, new optimized fabrication processes has been developed for the fabrication of NCD and III-N MEMS structures. These processing techniques was used to produce structures that led to the determination of the main mechanical properties and device parameters needed for MEMS design. Lastly, the gathered data was used for the design of various optimized demonstrator devices.

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.

Highly sensitive biological and chemical sensors based on reversible fluorescence quenching in a conjugated polymer

The fluorescence of a polyanionic conjugated polymer can be quenched by extremely low concentrations of cationic electron acceptors in aqueous solutions. We report a greater than million-fold amplification of the sensitivity to fluorescence quenching compared with corresponding “molecular excited states.” Using a combination of steady-state and ultrafast spectroscopy, we have established that the dramatic quenching results from weak complex formation [polymer(−)/quencher(+)], followed by ultrafast electron transfer from excitations on the entire polymer chain to the quencher, with a time constant of 650 fs. Because of the weak complex formation, the quenching can be selectively reversed by using a quencher-recognition diad. We have constructed such a diad and demonstrate that the fluorescence is fully recovered on binding between the recognition site and a specific analyte protein. In both solutions and thin films, this reversible fluorescence quenching provides the basis for a new class of highly sensitive biological and chemical sensors.