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.

Contribuciones en sistemas de adquisición de datos inteligentes para entornos de fusión por confinamiento magnético

Los sistemas de adquisición de datos utilizados en los diagnósticos de los dispositivos de fusión termonuclear se enfrentan a importantes retos planteados en los dispositivos de pulso largo. Incluso en los dispositivos de pulso corto, en los que se analizan los datos después de la descarga, existen aún una gran cantidad de datos sin analizar, lo cual supone que queda una gran cantidad de conocimiento por descubrir dentro de las bases de datos existentes. En la última década, la comunidad de fusión ha realizado un gran esfuerzo para mejorar los métodos de análisis off‐line para mejorar este problema, pero no se ha conseguido resolver completamente, debido a que algunos de estos métodos han de resolverse en tiempo real. Este paradigma lleva a establecer que los dispositivos de pulso largo deberán incluir dispositivos de adquisición de datos con capacidades de procesamiento local, capaces de ejecutar avanzados algoritmos de análisis. Los trabajos de investigación realizados en esta tesis tienen como objetivo determinar si es posible incrementar la capacidad local de procesamiento en tiempo real de dichos sistemas mediante el uso de GPUs. Para ello durante el trascurso del periodo de experimentación realizado se han evaluado distintas propuestas a través de casos de uso reales elaborados para algunos de los dispositivos de fusión más representativos como ITER, JET y TCV. Las conclusiones y experiencias obtenidas en dicha fase han permitido proponer un modelo y una metodología de desarrollo para incluir esta tecnología en los sistemas de adquisición para diagnósticos de distinta naturaleza. El modelo define no sólo la arquitectura hardware óptima para realizar dicha integración, sino también la incorporación de este nuevo recurso de procesamiento en los Sistemas de Control de Supervisión y Adquisición de Datos (SCADA) utilizados en la comunidad de fusión (EPICS), proporcionando una solución completa. La propuesta se complementa con la definición de una metodología que resuelve las debilidades detectadas, y permite trazar un camino de integración de la solución en los estándares hardware y software existentes. La evaluación final se ha realizado mediante el desarrollo de un caso de uso representativo de los diagnósticos que necesitan adquisición y procesado de imágenes en el contexto del dispositivo internacional ITER, y ha sido testeada con éxito en sus instalaciones. La solución propuesta en este trabajo ha sido incluida por la ITER IO en su catálogo de soluciones estándar para el desarrollo de sus futuros diagnósticos. Por otra parte, como resultado y fruto de la investigación de esta tesis, cabe destacar el acuerdo llevado a cabo con la empresa National Instruments en términos de transferencia tecnológica, lo que va a permitir la actualización de los sistemas de adquisición utilizados en los dispositivos de fusión. ABSTRACT Data acquisition systems used in the diagnostics of thermonuclear fusion devices face important challenges due to the change in the data acquisition paradigm needed for long pulse operation. Even in shot pulse devices, where data is mainly analyzed after the discharge has finished , there is still a large amount of data that has not been analyzed, therefore producing a lot of buried knowledge that still lies undiscovered in the data bases holding the vast amount of data that has been generated. There has been a strong effort in the fusion community in the last decade to improve the offline analysis methods to overcome this problem, but it has proved to be insufficient unless some of these mechanisms can be run in real time. In long pulse devices this new paradigm, where data acquisition devices include local processing capabilities to be able to run advanced data analysis algorithms, will be a must. The research works done in this thesis aim to determining whether it is possible to increase local capacity for real‐time processing of such systems by using GPUs. For that, during the experimentation period, various proposals have been evaluated through use cases developed for several of the most representative fusion devices, ITER, JET and TCV. Conclusions and experiences obtained have allowed to propose a model, and a development methodology, to include this technology in systems for diagnostics of different nature. The model defines not only the optimal hardware architecture for achieving this integration, but also the incorporation of this new processing resource in one of the Systems of Supervision Control and Data Acquisition (SCADA) systems more relevant at the moment in the fusion community (EPICS), providing a complete solution. The final evaluation has been performed through a use case developed for a generic diagnostic requiring image acquisition and processing for the international ITER device, and has been successfully tested in their premises. The solution proposed in this thesis has been included by the ITER IO in his catalog of standard solutions for the development of their future diagnostics. This has been possible thanks to the technologic transfer agreement signed with xi National Instruments which has permitted us to modify and update one of their core software products targeted for the acquisition systems used in these devices.

Monitorización de estructuras aeronáuticas mediante técnicas de inteligencia artificial

Una de las barreras para la aplicación de las técnicas de monitorización de la integridad estructural (SHM) basadas en ondas elásticas guiadas (GLW) en aeronaves es la influencia perniciosa de las condiciones ambientales y de operación (EOC). En esta tesis se ha estudiado dicha influencia y la compensación de la misma, particularizando en variaciones del estado de carga y temperatura. La compensación de dichos efectos se fundamenta en Redes Neuronales Artificiales (ANN) empleando datos experimentales procesados con la Transformada Chirplet. Los cambios en la geometría y en las propiedades del material respecto al estado inicial de la estructura (lo daños) provocan cambios en la forma de onda de las GLW (lo que denominamos característica sensible al daño o DSF). Mediante técnicas de tratamiento de señal se puede buscar una relación entre dichas variaciones y los daños, esto se conoce como SHM. Sin embargo, las variaciones en las EOC producen también cambios en los datos adquiridos relativos a las GLW (DSF) que provocan errores en los algoritmos de diagnóstico de daño (SHM). Esto sucede porque las firmas de daño y de las EOC en la DSF son del mismo orden. Por lo tanto, es necesario cuantificar y compensar el efecto de las EOC sobre la GLW. Si bien existen diversas metodologías para compensar los efectos de las EOC como por ejemplo “Optimal Baseline Selection” (OBS) o “Baseline Signal Stretching” (BSS), estas, se emplean exclusivamente en la compensación de los efectos térmicos. El método propuesto en esta tesis mezcla análisis de datos experimentales, como en el método OBS, y modelos basados en Redes Neuronales Artificiales (ANN) que reemplazan el modelado físico requerido por el método BSS. El análisis de datos experimentales consiste en aplicar la Transformada Chirplet (CT) para extraer la firma de las EOC sobre la DSF. Con esta información, obtenida bajo diversas EOC, se entrena una ANN. A continuación, la ANN actuará como un interpolador de referencias de la estructura sin daño, generando información de referencia para cualquier EOC. La comparación de las mediciones reales de la DSF con los valores simulados por la ANN, dará como resultado la firma daño en la DSF, lo que permite el diagnóstico de daño. Este esquema se ha aplicado y verificado, en diversas EOC, para una estructura unidimensional con un único camino de daño, y para una estructura representativa de un fuselaje de una aeronave, con curvatura y múltiples elementos rigidizadores, sometida a un estado de cargas complejo, con múltiples caminos de daños. Los efectos de las EOC se han estudiado en detalle en la estructura unidimensional y se han generalizado para el fuselaje, demostrando la independencia del método respecto a la configuración de la estructura y el tipo de sensores utilizados para la adquisición de datos GLW. Por otra parte, esta metodología se puede utilizar para la compensación simultánea de una variedad medible de EOC, que afecten a la adquisición de datos de la onda elástica guiada. El principal resultado entre otros, de esta tesis, es la metodología CT-ANN para la compensación de EOC en técnicas SHM basadas en ondas elásticas guiadas para el diagnóstico de daño. ABSTRACT One of the open problems to implement Structural Health Monitoring techniques based on elastic guided waves in real aircraft structures at operation is the influence of the environmental and operational conditions (EOC) on the damage diagnosis problem. This thesis deals with the compensation of these environmental and operational effects, specifically, the temperature and the external loading, by the use of the Chirplet Transform working with Artificial Neural Networks. It is well known that the guided elastic wave form is affected by the damage appearance (what is known as the damage sensitive feature or DSF). The DSF is modified by the temperature and by the load applied to the structure. The EOC promotes variations in the acquired data (DSF) and cause mistakes in damage diagnosis algorithms. This effect promotes changes on the waveform due to the EOC variations of the same order than the damage occurrence. It is difficult to separate both effects in order to avoid damage diagnosis mistakes. Therefore it is necessary to quantify and compensate the effect of EOC over the GLW forms. There are several approaches to compensate the EOC effects such as Optimal Baseline Selection (OBS) or Baseline Signal Stretching (BSS). Usually, they are used for temperature compensation. The new method proposed here mixes experimental data analysis, as in the OBS method, and Artificial Neural Network (ANN) models to replace the physical modelling which involves the BSS method. The experimental data analysis studied is based on apply the Chirplet Transform (CT) to extract the EOC signature on the DSF. The information obtained varying EOC is employed to train an ANN. Then, the ANN will act as a baselines interpolator of the undamaged structure. The ANN generates reference information at any EOC. By comparing real measurements of the DSF against the ANN simulated values, the damage signature appears clearly in the DSF, enabling an accurate damage diagnosis. This schema has been applied in a range of EOC for a one-dimensional structure containing single damage path and two dimensional real fuselage structure with stiffener elements and multiple damage paths. The EOC effects tested in the one-dimensional structure have been generalized to the fuselage showing its independence from structural arrangement and the type of sensors used for GLW data acquisition. Moreover, it can be used for the simultaneous compensation of a variety of measurable EOC, which affects the guided wave data acquisition. The main result, among others, of this thesis is the CT-ANN methodology for the compensation of EOC in GLW based SHM technique for damage diagnosis.

Las Redes de Petri Interpretadas en el Diagnóstico de Fallos de Sistemas Híbridos. Aplicación a un Helicóptero no Tripulado

La seguridad y fiabilidad de los procesos industriales son la principal preocupación de los ingenieros encargados de las plantas industriales. Por lo tanto, desde un punto de vista económico, el objetivo principal es reducir el costo del mantenimiento, el tiempo de inactividad y las pérdidas causadas por los fallos. Por otra parte, la seguridad de los operadores, que afecta a los aspectos sociales y económicos, es el factor más relevante a considerar en cualquier sistema Debido a esto, el diagnóstico de fallos se ha convertido en un foco importante de interés para los investigadores de todo el mundo e ingenieros en la industria. Los principales trabajos enfocados en detección de fallos se basan en modelos de los procesos. Existen diferentes técnicas para el modelado de procesos industriales tales como máquinas de estado, árboles de decisión y Redes de Petri (RdP). Por lo tanto, esta tesis se centra en el modelado de procesos utilizando redes de petri interpretadas. Redes de Petri es una herramienta usada en el modelado gráfico y matemático con la habilidad para describir información de los sistemas de una manera concurrente, paralela, asincrona, distribuida y no determinística o estocástica. RdP son también una herramienta de comunicación visual gráfica útil como lo son las cartas de flujo o diagramas de bloques. Adicionalmente, las marcas de las RdP simulan la dinámica y concurrencia de los sistemas. Finalmente, ellas tienen la capacidad de definir ecuaciones de estado específicas, ecuaciones algebraicas y otros modelos que representan el comportamiento común de los sistemas. Entre los diferentes tipos de redes de petri (Interpretadas, Coloreadas, etc.), este trabajo de investigación trata con redes de petri interpretadas principalmente debido a características tales como sincronización, lugares temporizados, aparte de su capacidad para procesamiento de datos. Esta investigación comienza con el proceso para diseñar y construir el modelo y diagnosticador para detectar fallos definitivos, posteriormente, la dinámica temporal fue adicionada para detectar fallos intermitentes. Dos procesos industriales, concretamente un HVAC (Calefacción, Ventilación y Aire Acondicionado) y un Proceso de Envasado de Líquidos fueron usados como banco de pruebas para implementar la herramienta de diagnóstico de fallos (FD) creada. Finalmente, su capacidad de diagnóstico fue ampliada en orden a detectar fallos en sistemas híbridos. Finalmente, un pequeño helicóptero no tripulado fue elegido como ejemplo de sistema donde la seguridad es un desafío, y las técnicas de detección de fallos desarrolladas en esta tesis llevan a ser una herramienta valorada, desde que los accidentes de las aeronaves no tripuladas (UAVs) envuelven un alto costo económico y son la principal razón para introducir restricciones de volar sobre áreas pobladas. Así, este trabajo introduce un proceso sistemático para construir un Diagnosticador de Fallos del sistema mencionado basado en RdR Esta novedosa herramienta es capaz de detectar fallos definitivos e intermitentes. El trabajo realizado es discutido desde un punto de vista teórico y práctico. El procedimiento comienza con la división del sistema en subsistemas para seguido integrar en una RdP diagnosticadora global que es capaz de monitorear el sistema completo y mostrar las variables críticas al operador en orden a determinar la salud del UAV, para de esta manera prevenir accidentes. Un Sistema de Adquisición de Datos (DAQ) ha sido también diseñado para recoger datos durante los vuelos y alimentar la RdP diagnosticadora. Vuelos reales realizados bajo condiciones normales y de fallo han sido requeridos para llevar a cabo la configuración del diagnosticador y verificar su comportamiento. Vale la pena señalar que un alto riesgo fue asumido en la generación de fallos durante los vuelos, a pesar de eso esto permitió recoger datos básicos para desarrollar el diagnóstico de fallos, técnicas de aislamiento, protocolos de mantenimiento, modelos de comportamiento, etc. Finalmente, un resumen de la validación de resultados obtenidos durante las pruebas de vuelo es también incluido. Un extensivo uso de esta herramienta mejorará los protocolos de mantenimiento para UAVs (especialmente helicópteros) y permite establecer recomendaciones en regulaciones. El uso del diagnosticador usando redes de petri es considerado un novedoso enfoque. ABSTRACT Safety and reliability of industrial processes are the main concern of the engineers in charge of industrial plants. Thus, from an economic point of view, the main goal is to reduce the maintenance downtime cost and the losses caused by failures. Moreover, the safety of the operators, which affects to social and economic aspects, is the most relevant factor to consider in any system. Due to this, fault diagnosis has become a relevant focus of interest for worldwide researchers and engineers in the industry. The main works focused on failure detection are based on models of the processes. There are different techniques for modelling industrial processes such as state machines, decision trees and Petri Nets (PN). Thus, this Thesis is focused on modelling processes by using Interpreted Petri Nets. Petri Nets is a tool used in the graphic and mathematical modelling with ability to describe information of the systems in a concurrent, parallel, asynchronous, distributed and not deterministic or stochastic manner. PNs are also useful graphical visual communication tools as flow chart or block diagram. Additionally, the marks of the PN simulate the dynamics and concurrence of the systems. Finally, they are able to define specific state equations, algebraic equations and other models that represent the common behaviour of systems. Among the different types of PN (Interpreted, Coloured, etc.), this research work deals with the interpreted Petri Nets mainly due to features such as synchronization capabilities, timed places, apart from their capability for processing data. This Research begins with the process for designing and building the model and diagnoser to detect permanent faults, subsequently, the temporal dynamic was added for detecting intermittent faults. Two industrial processes, namely HVAC (Heating, Ventilation and Air Condition) and Liquids Packaging Process were used as testbed for implementing the Fault Diagnosis (FD) tool created. Finally, its diagnostic capability was enhanced in order to detect faults in hybrid systems. Finally, a small unmanned helicopter was chosen as example of system where safety is a challenge and fault detection techniques developed in this Thesis turn out to be a valuable tool since UAVs accidents involve high economic cost and are the main reason for setting restrictions to fly over populated areas. Thus, this work introduces a systematic process for building a Fault Diagnoser of the mentioned system based on Petri Nets. This novel tool is able to detect both intermittent and permanent faults. The work carried out is discussed from theoretical and practical point of view. The procedure begins with a division of the system into subsystems for further integration into a global PN diagnoser that is able to monitor the whole system and show critical variables to the operator in order to determine the UAV health, preventing accidents in this manner. A Data Acquisition System (DAQ) has been also designed for collecting data during the flights and feed PN Diagnoser. Real flights carried out under nominal and failure conditions have been required to perform the diagnoser setup and verify its performance. It is worth noting that a high risk was assumed in the generation of faults during the flights, nevertheless this allowed collecting basic data so as to develop fault diagnosis, isolations techniques, maintenance protocols, behaviour models, etc. Finally, a summary of the validation results obtained during real flight tests is also included. An extensive use of this tool will improve preventive maintenance protocols for UAVs (especially helicopters) and allow establishing recommendations in regulations. The use of the diagnoser by using Petri Nets is considered as novel approach.

Prototipo experimental para implementar las solicitaciones del viento en los buques amarrados. Aplicación a un crucero

Habitualmente en los ensayos de barcos amarrados se reproduce la acción del oleaje. Se ha diseñado un sistema para la reproducción del efecto del viento en estos ensayos, utilizando motores, poleas, hilos de conexión, muelles, galgas y controladoras, de forma que la fuerza ejercida por el viento, previamente calculada considerando las características del barco y del viento, se transmite al barco mediante los elementos que componen el sistema. Este sistema consiste en un circuito cerrado de transmisión de fuerza con un motor que simultáneamente actúa sobre dos muelles deformándolos en sentidos opuestos, los cuales transmiten las fuerzas en los costados del buque, siendo la diferencia del alargamiento de los muelles la fuerza resultante sobre el barco. El sistema se aplicó a un buque crucero, obteniendo unos resultados que muestran la importancia de tener en cuenta el viento racheado como un agente adicional al oleaje que provoca movimientos y esfuerzos en las amarras y defensas elevados, dependiendo de su intensidad y dirección. Se ensayaron tres condiciones: modelo alimentado únicamente con olas, solo con viento y con ambos. En cada ensayo realizado se registraron los movimientos del buque, las fuerzas en las amarras y las reacciones en las defensas. La aportación de la Tesis es un sistema mecánico para excitar el modelo del buque amarrado con viento racheado superpuesto a la acción del oleaje. Evidentemente los resultados que se obtengan se ajustarán más a la situación real que reproduciendo sólo el oleaje. ABSTRACT Traditionally, moored ship tests with small-scale models only take into account the disturbance effect of waves. In this thesis, the design and testing of a system also implementing the effect of wind in moored ships is analyzed. The system is based on rotatory actuators acting on linear springs. This solution has a swift enough response to reproduce the fluctuating component of the wind. Three scenarios have been tested: waves, wind and combination of both. In order to assess the results, different sensors are connected to a computer for data acquisition, allowing the recording and subsequent analysis of the measured variables (forces in ropes, reactions in fenders and ship motions). The results obtained from the experiments show a great impact when wind effect is considered. A superposition effect is observed when waves and wind act together on the ship, emphasizing therefore the importance of taking the wind into account in berthed vessel tests, achieving safer and more realistic results.

Desarrollo de software de control y medida para goniofotómetro de tipo B

El proyecto trata del desarrollo de un software para realizar el control de la medida de la distribución de intensidad luminosa en luminarias LED. En el trascurso del proyecto se expondrán fundamentos teóricos sobre fotometría básica, de los cuales se extraen las condiciones básicas para realizar dicha medida. Además se realiza una breve descripción del hardware utilizado en el desarrollo de la máquina, el cual se basa en una placa de desarrollo Arduino Mega 2560, que, gracias al paquete de Labview “LIFA” (Labview Interface For Arduino”), será posible utilizarla como tarjeta de adquisición de datos mediante la cual poder manejar tanto sensores como actuadores, para las tareas de control. El instrumento de medida utilizado en este proyecto es el BTS256 de la casa GigaHerzt-Optik, del cual se dispone de un kit de desarrollo tanto en lenguaje C++ como en Labview, haciendo posible programar aplicaciones basadas en este software para realizar cualquier tipo de adaptación a las necesidades del proyecto. El software está desarrollado en la plataforma Labview 2013, esto es gracias a que se dispone del kit de desarrollo del instrumento de medida, y del paquete LIFA. El objetivo global del proyecto es realizar la caracterización de luminarias LED, de forma que se obtengan medidas suficientes de la distribución de intensidad luminosa. Los datos se recogerán en un archivo fotométrico específico, siguiendo la normativa IESNA 2002 sobre formato de archivos fotométricos, que posteriormente será utilizado en la simulación y estudio de instalaciones reales de la luminaria. El sistema propuesto en este proyecto, es un sistema basado en fotometría tipo B, utilizando coordenadas VH, desarrollando un algoritmo de medida que la luminaria describa un ángulo de 180º en ambos ejes, con una resolución de 5º para el eje Vertical y 22.5º para el eje Horizontal, almacenando los datos en un array que será escrito en el formato exigido por la normativa. Una vez obtenidos los datos con el instrumento desarrollado, el fichero generado por la medida, es simulado con el software DIALux, obteniendo unas medidas de iluminación en la simulación que serán comparadas con las medidas reales, intentando reproducir en la simulación las condiciones reales de medida. ABSTRACT. The project involves the development of software for controlling the measurement of light intensity distribution in LEDs. In the course of the project theoretical foundations on basic photometry, of which the basic conditions for such action are extracted will be presented. Besides a brief description of the hardware used in the development of the machine, which is based on a Mega Arduino plate 2560 is made, that through the package Labview "LIFA" (Interface For Arduino Labview "), it is possible to use as data acquisition card by which to handle both sensors and actuators for control tasks. The instrument used in this project is the BTS256 of GigaHerzt-Optik house, which is available a development kit in both C ++ language as LabView, making it possible to program based on this software applications for any kind of adaptation to project needs. The software is developed in Labview 2013 platform, this is thanks to the availability of the SDK of the measuring instrument and the LIFA package. The overall objective of the project is the characterization of LED lights, so that sufficient measures the light intensity distribution are obtained. Data will be collected on a specific photometric file, following the rules IESNA 2002 on photometric format files, which will then be used in the simulation and study of actual installations of the luminaire. The proposed in this project is a system based on photometry type B system using VH coordinates, developing an algorithm as the fixture describe an angle of 180 ° in both axes, with a resolution of 5 ° to the vertical axis and 22.5º for the Horizontal axis, storing data in an array to be written in the format required by the regulations. After obtaining the data with the instrument developed, the file generated by the measure, is simulated with DIALux software, obtaining measures of lighting in the simulation will be compared with the actual measurements, trying to play in the simulation the actual measurement conditions .

Systematic Process for Building a Fault Diagnoser Based on Petri Nets Applied to a Helicopter

This work presents a systematic process for building a Fault Diagnoser (FD), based on Petri Nets (PNs) which has been applied to a small helicopter. This novel tool is able to detect both intermittent and permanent faults. The work carried out is discussed from theoretical and practical point of view. The procedure begins with a division of the whole system into subsystems, which are the devices that have to be modeled by using PN, considering both the normal and fault operations. Subsequently, the models are integrated into a global Petri Net diagnoser (PND) that is able to monitor a whole helicopter and show critical variables to the operator in order to determine the UAV health, preventing accidents in this manner. A Data Acquisition System (DAQ) has been designed for collecting data during the flights and feeding PN diagnoser with them. Several real flights (nominal or under failure) have been carried out to perform the diagnoser setup and verify its performance. A summary of the validation results obtained during real flight tests is also included. An extensive use of this tool will improve preventive maintenance protocols for UAVs (especially helicopters) and allow establishing recommendations in regulations

Climate and infectious disease: Use of remote sensing for detection of Vibrio cholerae by indirect measurement

It has long been known that cholera outbreaks can be initiated when Vibrio cholerae, the bacterium that causes cholera, is present in drinking water in sufficient numbers to constitute an infective dose, if ingested by humans. Outbreaks associated with drinking or bathing in unpurified river or brackish water may directly or indirectly depend on such conditions as water temperature, nutrient concentration, and plankton production that may be favorable for growth and reproduction of the bacterium. Although these environmental parameters have routinely been measured by using water samples collected aboard research ships, the available data sets are sparse and infrequent. Furthermore, shipboard data acquisition is both expensive and time-consuming. Interpolation to regional scales can also be problematic. Although the bacterium, V. cholerae, cannot be sensed directly, remotely sensed data can be used to infer its presence. In the study reported here, satellite data were used to monitor the timing and spread of cholera. Public domain remote sensing data for the Bay of Bengal were compared directly with cholera case data collected in Bangladesh from 1992–1995. The remote sensing data included sea surface temperature and sea surface height. It was discovered that sea surface temperature shows an annual cycle similar to the cholera case data. Sea surface height may be an indicator of incursion of plankton-laden water inland, e.g., tidal rivers, because it was also found to be correlated with cholera outbreaks. The extensive studies accomplished during the past 25 years, confirming the hypothesis that V. cholerae is autochthonous to the aquatic environment and is a commensal of zooplankton, i.e., copepods, when combined with the findings of the satellite data analyses, provide strong evidence that cholera epidemics are climate-linked.

Controle de uma plataforma inercial estabilizada com três graus de liberdade.

Esta dissertação apresenta o desenvolvimento de uma plataforma inercial autônoma com três graus de liberdade para aplicação em estabilização de sensores - por exemplo, gravimétricos estacionários e embarcados - podendo ser utilizada também para estabilização de câmeras. O sistema é formado pela Unidade de Medida Inercial, IMU, desenvolvida utilizando um sensor micro eletromecânico, MEMS - que possui acelerômetro, giroscópio e magnetômetros nos três eixos de orientação - e um microcontrolador para aquisição, processamento e envio dos dados ao sistema de controle e aquisição de dados. Para controle dos ângulos de inclinação e orientação da plataforma, foi implementado um controlador PID digital utilizando microcontrolador. Este recebe os dados da IMU e fornece os sinais de controle utilizando as saídas PWM que acionam os motores, os quais controlam a posição da plataforma. Para monitoramento da plataforma foi desenvolvido um programa para aquisição de dados em tempo real em ambiente Matlab, por meio do qual se pode visualizar e gravar os sinais da IMU, os ângulos de inclinação e a velocidade angular. Testou-se um sistema de transmissão de dados por rádio frequência entre a IMU e o sistema de aquisição de dados e controle para avaliar a possibilidade da não utilização de slip rings ou fios entre o eixo de rotação e os quadros da plataforma. Entretanto, verificou-se a inviabilidade da transmissão em razão da baixa velocidade de transmissão e dos ruídos captados pelo receptor de rádio frequência durante osmovimentos da plataforma. Sendo assim, dois pares de fios trançados foram utilizados fios para conectar o sensor inercial ao sistema de aquisição e processamento.

Reconciliação de dados de uma malha de gasodutos.

O trabalho aborda a aplicação da técnica de reconciliação de dados para o balanço da movimentação de gás natural em uma malha de escoamento de gás não processado, elaborando também um método de cálculo rápido de inventário de um duto. Foram aplicadas, separadamente, a reconciliação volumétrica à condição padrão de medição e a reconciliação mássica, bem como realizadas comparações dos resultados em relação ao balanço original e verificação do balanço resultante de energia em termos de poder calorífico superior. Dois conjuntos de pesos foram aplicados, um arbitrado de acordo com o conhecimento prévio da qualidade do sistema de medição de cada um dos pontos, outro baseado no inverso da variância dos volumes diários apurados no período. Ambos apresentaram bons resultados e o segundo foi considerado o mais apropriado. Por meio de uma abordagem termodinâmica, foi avaliado o potencial impacto, ao balanço, da condensação de parte da fase gás ao longo do escoamento e a injeção de um condensado de gás natural não estabilizado por uma das fontes. Ambos tendem a impactar o balanço, sendo o resultado esperado um menor volume, massa e energia de fase gás na saída. Outros fatores de considerável impacto na qualidade dos dados e no resultado final da reconciliação são a qualidade da medição de saída do sistema e a representatividade da composição do gás neste ponto. O inventário é calculado a partir de uma regressão que se baseia em um regime permanente de escoamento, o que pode apresentar maior desvio quando fortes transientes estão ocorrendo no último dia do mês, porém a variação de inventário ao longo do mês possui baixo impacto no balanço. Concluiu-se que a reconciliação volumétrica é a mais apropriada para este sistema, pois os dados reconciliados levam os balanços mássicos e de energia em termos de poder calorífico, ambos na fase gás, para dentro do perfil esperado de comportamento. Embora um balanço volumétrico nulo apenas da fase gás não seja por si só o comportamento esperado quando se considera os efeitos descritos, para desenvolver um balanço mais robusto é necessário considerar as frações líquidas presentes no sistema, agregando maior dificuldade na aquisição e qualidade dos dados.

Sistema especialista para análise pós-evento da proteção em subestações distribuidoras.

É importante que as redes elétricas tenham altos índices de confiabilidade, de forma a se manter a agilidade e a manutenção ideais para um melhor funcionamento. Por outro lado, o crescimento inesperado da carga, falhas em equipamentos e uma parametrização inadequada das funções de proteção tornam a análise de eventos de proteção mais complexas e demoradas. Além disso, a quantidade de informações que pode ser obtida de relés digitais modernos tem crescido constantemente. Para que seja possível uma rápida tomada de decisão e manutenção, esse projeto de pesquisa teve como objetivo a implementação de um sistema completo de diagnóstico que é ativado automaticamente quando um evento de proteção ocorrer. As informações a serem analisadas são obtidas de uma base de dados e de relés de proteção, via protocolo de comunicação IEC 61850 e arquivos de oscilografia. O trabalho aborda o sistema Smart Grid completo incluindo: a aquisição de dados nos relés, detalhando o sistema de comunicação desenvolvido através de um software com um cliente IEC61850 e um servidor OPC e um software com um cliente OPC, que é ativado por eventos configurados para dispará-lo (por exemplo, atuação da proteção); o sistema de pré-tratamento de dados, onde os dados provenientes dos relés e equipamentos de proteção são filtrados, pré-processados e formatados; e o sistema de diagnóstico. Um banco de dados central mantém atualizados os dados de todas essas etapas. O sistema de diagnóstico utiliza algoritmos convencionais e técnicas de inteligência artificial, em particular, um sistema especialista. O sistema especialista foi desenvolvido para lidar com diferentes conjuntos de dados de entrada e com uma possível falta de dados, sempre garantindo a entrega de diagnósticos. Foram realizados testes e simulações para curtos-circuitos (trifásico, dupla-fase, dupla-fase-terra e fase-terra) em alimentadores, transformadores e barras de uma subestação. Esses testes incluíram diferentes estados do sistema de proteção (funcionamento correto e impróprio). O sistema se mostrou totalmente eficaz tanto no caso de disponibilidade completa quanto parcial de informações, sempre fornecendo um diagnóstico do curto-circuito e analisando o funcionamento das funções de proteção da subestação. Dessa forma, possibilita-se uma manutenção muito mais eficiente pelas concessionárias de energia, principalmente no que diz respeito à prevenção de defeitos em equipamentos, rápida resposta a problemas, e necessidade de reparametrização das funções de proteção. O sistema foi instalado com sucesso em uma subestação de distribuição da Companhia Paulista de Força e Luz.

A new approach for semi-automatic rock mass joints recognition from 3D point clouds

Rock mass characterization requires a deep geometric understanding of the discontinuity sets affecting rock exposures. Recent advances in Light Detection and Ranging (LiDAR) instrumentation currently allow quick and accurate 3D data acquisition, yielding on the development of new methodologies for the automatic characterization of rock mass discontinuities. This paper presents a methodology for the identification and analysis of flat surfaces outcropping in a rocky slope using the 3D data obtained with LiDAR. This method identifies and defines the algebraic equations of the different planes of the rock slope surface by applying an analysis based on a neighbouring points coplanarity test, finding principal orientations by Kernel Density Estimation and identifying clusters by the Density-Based Scan Algorithm with Noise. Different sources of information —synthetic and 3D scanned data— were employed, performing a complete sensitivity analysis of the parameters in order to identify the optimal value of the variables of the proposed method. In addition, raw source files and obtained results are freely provided in order to allow to a more straightforward method comparison aiming to a more reproducible research.

Towards a real-time 3D object recognition pipeline on mobile GPGPU computing platforms using low-cost RGB-D sensors

In this project, we propose the implementation of a 3D object recognition system which will be optimized to operate under demanding time constraints. The system must be robust so that objects can be recognized properly in poor light conditions and cluttered scenes with significant levels of occlusion. An important requirement must be met: the system must exhibit a reasonable performance running on a low power consumption mobile GPU computing platform (NVIDIA Jetson TK1) so that it can be integrated in mobile robotics systems, ambient intelligence or ambient assisted living applications. The acquisition system is based on the use of color and depth (RGB-D) data streams provided by low-cost 3D sensors like Microsoft Kinect or PrimeSense Carmine. The range of algorithms and applications to be implemented and integrated will be quite broad, ranging from the acquisition, outlier removal or filtering of the input data and the segmentation or characterization of regions of interest in the scene to the very object recognition and pose estimation. Furthermore, in order to validate the proposed system, we will create a 3D object dataset. It will be composed by a set of 3D models, reconstructed from common household objects, as well as a handful of test scenes in which those objects appear. The scenes will be characterized by different levels of occlusion, diverse distances from the elements to the sensor and variations on the pose of the target objects. The creation of this dataset implies the additional development of 3D data acquisition and 3D object reconstruction applications. The resulting system has many possible applications, ranging from mobile robot navigation and semantic scene labeling to human-computer interaction (HCI) systems based on visual information.

Comparison among monitoring strategies to assess water flow dynamic and soil hydraulic properties in agricultural soils

Irrigated agriculture is usually performed in semi-arid regions despite scarcity of water resources. Therefore, optimal irrigation management by monitoring the soil is essential, and assessing soil hydraulic properties and water flow dynamics is presented as a first measure. For this purpose, the control of volumetric water content, θ, and pressure head, h, is required. This study adopted two types of monitoring strategies in the same experimental plot to control θ and h in the vadose zone: i) non-automatic and more time-consuming; ii) automatic connected to a datalogger. Water flux was modelled with Hydrus-1D using the data collected from both acquisition strategies independently (3820 daily values for the automatic; less than 1000 for the non-automatic). Goodness-of-fit results reported a better adjustment in case of automatic sensors. Both model outputs adequately predicted the general trend of θ and h, but with slight differences in computed annual drainage (711 mm and 774 mm). Soil hydraulic properties were inversely estimated from both data acquisition systems. Major differences were obtained in the saturated volumetric water content, θs, and the n and α van Genuchten model shape parameters. Saturated hydraulic conductivity, Ks, shown lower variability with a coefficient of variation range from 0.13 to 0.24 for the soil layers defined. Soil hydraulic properties were better assessed through automatic data acquisition as data variability was lower and accuracy was higher.

Development and programming of Geophonino: A low cost Arduino-based seismic recorder for vertical geophones

The commercial data acquisition systems used for seismic exploration are usually expensive equipment. In this work, a low cost data acquisition system (Geophonino) has been developed for recording seismic signals from a vertical geophone. The signal goes first through an instrumentation amplifier, INA155, which is suitable for low amplitude signals like the seismic noise, and an anti-aliasing filter based on the MAX7404 switched-capacitor filter. After that, the amplified and filtered signal is digitized and processed by Arduino Due and registered in an SD memory card. Geophonino is configured for continuous registering, where the sampling frequency, the amplitude gain and the registering time are user-defined. The complete prototype is an open source and open hardware system. It has been tested by comparing the registered signals with the ones obtained through different commercial data recording systems and different kind of geophones. The obtained results show good correlation between the tested measurements, presenting Geophonino as a low-cost alternative system for seismic data recording.