On the Analytical Approach to Present Engineering Problems: Photovoltaic Systems Behavior, Wind Speed Sensors Performance, and High-Speed Train Pressure Wave Effects in Tunnels

At present, engineering problems required quite a sophisticated calculation means. However, analytical models still can prove to be a useful tool for engineers and scientists when dealing with complex physical phenomena. The mathematical models developed to analyze three different engineering problems: photovoltaic devices analysis; cup anemometer performance; and high-speed train pressure wave effects in tunnels are described. In all cases, the results are quite accurate when compared to testing measurements.

Development of a human movement monitoring system based on wearable devices

It is essential to remotely and continuously monitor the movements of individuals in many social areas, for example, taking care of aging people, physical therapy, athletic training etc. Many methods have been used, such as video record, motion analysis or sensor-based methods. Due to the limitations in remote communication, power consumption, portability and so on, most of them are not able to fulfill the requirements. The development of wearable technology and cloud computing provides a new efficient way to achieve this goal. This paper presents an intelligent human movement monitoring system based on a smartwatch, an Android smartphone and a distributed data management engine. This system includes advantages of wide adaptability, remote and long-term monitoring capacity, high portability and flexibility. The structure of the system and its principle are introduced. Four experiments are designed to prove the feasibility of the system. The results of the experiments demonstrate the system is able to detect different actions of individuals with adequate accuracy.

On the harmonic analysis of cup anemometer rotation speed: A principle to monitor performance and maintenance status of rotating meteorological sensors

The calibration results of one anemometer equipped with several rotors, varying their size, were analyzed. In each case, the 30-pulses pert turn output signal of the anemometer was studied using Fourier series decomposition and correlated with the anemometer factor (i.e., the anemometer transfer function). Also, a 3-cup analytical model was correlated to the data resulting from the wind tunnel measurements. Results indicate good correlation between the post-processed output signal and the working condition of the cup anemometer. This correlation was also reflected in the results from the proposed analytical model. With the present work the possibility of remotely checking cup anemometer status, indicating the presence of anomalies and, therefore, a decrease on the wind sensor reliability is revealed.

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.

RETRATO DEL EX.MO É ILL.MO S.OR D.N FRAI JOAQUIN COMPANY [Material gráfico] : Caballero Gran Cruz de la Rl. distinguida Orden de Carlos III Arzobispo antes de Zaragoza y después de Valencia

Resumen: Descripción: retrato de 3/4 en el interior de un óvalo. Viste indumentaria de arzobispo. En el ángulo izqdo., la mitra y báculo

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.

Advanced Characterisation of a Coffee Fermenting Tank by Multi-distributed Wireless Sensors: Spatial Interpolation and Phase Space Graphs

The fermentation stage is considered to be one of the critical steps in coffee processing due to its impact on the final quality of the product. The objective of this work is to characterise the temperature gradients in a fermentation tank by multi-distributed, low-cost and autonomous wireless sensors (23 semi-passive TurboTag® radio-frequency identifier (RFID) temperature loggers). Spatial interpolation in polar coordinates and an innovative methodology based on phase space diagrams are used. A real coffee fermentation process was supervised in the Cauca region (Colombia) with sensors submerged directly in the fermenting mass, leading to a 4.6 °C temperature range within the fermentation process. Spatial interpolation shows a maximum instant radial temperature gradient of 0.1 °C/cm from the centre to the perimeter of the tank and a vertical temperature gradient of 0.25 °C/cm for sensors with equal polar coordinates. The combination of spatial interpolation and phase space graphs consistently enables the identification of five local behaviours during fermentation (hot and cold spots).

Contribution towards intelligent service management in wearable and ubiquitous devices

Hoy en día asistimos a un creciente interés por parte de la sociedad hacia el cuidado de la salud. Esta afirmación viene apoyada por dos realidades. Por una parte, el aumento de las prácticas saludables (actividad deportiva, cuidado de la alimentación, etc.). De igual manera, el auge de los dispositivos inteligentes (relojes, móviles o pulseras) capaces de medir distintos parámetros físicos como el pulso cardíaco, el ritmo respiratorio, la distancia recorrida, las calorías consumidas, etc. Combinando ambos factores (interés por el estado de salud y disponibilidad comercial de dispositivos inteligentes) están surgiendo multitud de aplicaciones capaces no solo de controlar el estado actual de salud, también de recomendar al usuario cambios de hábitos que lleven hacia una mejora en su condición física. En este contexto, los llamados dispositivos llevables (weareables) unidos al paradigma de Internet de las cosas (IoT, del inglés Internet of Things) permiten la aparición de nuevos nichos de mercado para aplicaciones que no solo se centran en la mejora de la condición física, ya que van más allá proponiendo soluciones para el cuidado de pacientes enfermos, la vigilancia de niños o ancianos, la defensa y la seguridad, la monitorización de agentes de riesgo (como bomberos o policías) y un largo etcétera de aplicaciones por llegar. El paradigma de IoT se puede desarrollar basándose en las existentes redes de sensores inalámbricos (WSN, del inglés Wireless Sensor Network). La conexión de los ya mencionados dispositivos llevables a estas redes puede facilitar la transición de nuevos usuarios hacia aplicaciones IoT. Pero uno de los problemas intrínsecos a estas redes es su heterogeneidad. En efecto, existen multitud de sistemas operativos, protocolos de comunicación, plataformas de desarrollo, soluciones propietarias, etc. El principal objetivo de esta tesis es realizar aportaciones significativas para solucionar no solo el problema de la heterogeneidad, sino también de dotar de mecanismos de seguridad suficientes para salvaguardad la integridad de los datos intercambiados en este tipo de aplicaciones. Algo de suma importancia ya que los datos médicos y biométricos de los usuarios están protegidos por leyes nacionales y comunitarias. Para lograr dichos objetivos, se comenzó con la realización de un completo estudio del estado del arte en tecnologías relacionadas con el marco de investigación (plataformas y estándares para WSNs e IoT, plataformas de implementación distribuidas, dispositivos llevables y sistemas operativos y lenguajes de programación). Este estudio sirvió para tomar decisiones de diseño fundamentadas en las tres contribuciones principales de esta tesis: un bus de servicios para dispositivos llevables (WDSB, Wearable Device Service Bus) basado en tecnologías ya existentes tales como ESB, WWBAN, WSN e IoT); un protocolo de comunicaciones inter-dominio para dispositivos llevables (WIDP, Wearable Inter-Domain communication Protocol) que integra en una misma solución protocolos capaces de ser implementados en dispositivos de bajas capacidades (como lo son los dispositivos llevables y los que forman parte de WSNs); y finalmente, la tercera contribución relevante es una propuesta de seguridad para WSN basada en la aplicación de dominios de confianza. Aunque las contribuciones aquí recogidas son de aplicación genérica, para su validación se utilizó un escenario concreto de aplicación: una solución para control de parámetros físicos en entornos deportivos, desarrollada dentro del proyecto europeo de investigación “LifeWear”. En este escenario se desplegaron todos los elementos necesarios para validar las contribuciones principales de esta tesis y, además, se realizó una aplicación para dispositivos móviles por parte de uno de los socios del proyecto (lo que contribuyó con una validación externa de la solución). En este escenario se usaron dispositivos llevables tales como un reloj inteligente, un teléfono móvil con sistema operativo Android y un medidor del ritmo cardíaco inalámbrico capaz de obtener distintos parámetros fisiológicos del deportista. Sobre este escenario se realizaron diversas pruebas de validación mediante las cuales se obtuvieron resultados satisfactorios. ABSTRACT Nowadays, society is shifting towards a growing interest and concern on health care. This phenomenon can be acknowledged by two facts: first, the increasing number of people practising some kind of healthy activity (sports, balanced diet, etc.). Secondly, the growing number of commercial wearable smart devices (smartwatches or bands) able to measure physiological parameters such as heart rate, breathing rate, distance or consumed calories. A large number of applications combining both facts are appearing. These applications are not only able to monitor the health status of the user, but also to provide recommendations about routines in order to improve the mentioned health status. In this context, wearable devices merged with the Internet of Things (IoT) paradigm enable the proliferation of new market segments for these health wearablebased applications. Furthermore, these applications can provide solutions for the elderly or baby care, in-hospital or in-home patient monitoring, security and defence fields or an unforeseen number of future applications. The introduced IoT paradigm can be developed with the usage of existing Wireless Sensor Networks (WSNs) by connecting the novel wearable devices to them. In this way, the migration of new users and actors to the IoT environment will be eased. However, a major issue appears in this environment: heterogeneity. In fact, there is a large number of operating systems, hardware platforms, communication and application protocols or programming languages, each of them with unique features. The main objective of this thesis is defining and implementing a solution for the intelligent service management in wearable and ubiquitous devices so as to solve the heterogeneity issues that are presented when dealing with interoperability and interconnectivity of devices and software of different nature. Additionally, a security schema based on trust domains is proposed as a solution to the privacy problems arising when private data (e.g., biomedical parameters or user identification) is broadcasted in a wireless network. The proposal has been made after a comprehensive state-of-the-art analysis, and includes the design of a Wearable Device Service Bus (WDSB) including the technologies collected in the requirement analysis (ESB, WWBAN, WSN and IoT). Applications are able to access the WSN services regardless of the platform and operating system where they are running. Besides, this proposal also includes the design of a Wearable Inter-Domain communication Protocols set (WIDP) which integrates lightweight protocols suitable to be used in low-capacities devices (REST, JSON, AMQP, CoAP, etc...). Furthermore, a security solution for service management based on a trustworthy domains model to deploy security services in WSNs has been designed. Although the proposal is a generic framework for applications based on services provided by wearable devices, an application scenario for testing purposes has been included. In this validation scenario it has been presented an autonomous physical condition performance system, based on a WSN, bringing the possibility to include several elements in an IoT scenario: a smartwatch, a physiological monitoring device and a smartphone. In summary, the general objective of this thesis is solving the heterogeneity and security challenges arising when developing applications for WSNs and wearable devices. As it has been presented in the thesis, the solution proposed has been successfully validated in a real scenario and the obtained results were satisfactory.

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.

Influence of body weight support on wearable devices reproducing normal gait

Oral presentation en ESMAC 2015

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.

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.