58 resultados para Data acquisition.

em Universidad Politécnica de Madrid


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A small Positron Emission Tomography demonstrator based on LYSO slabs and Silicon Photomultiplier matrices is under construction at the University and INFN of Pisa. In this paper we present the characterization results of the read-out electronics and of the detection system. Two SiPM matrices, composed by 8 × 8 SiPM pixels, 1.5 mm pitch, have been coupled one to one to a LYSO crystals array. Custom Front-End ASICs were used to read the 64 channels of each matrix. Data from each Front-End were multiplexed and sent to a DAQ board for the digital conversion; a motherboard collects the data and communicates with a host computer through a USB port. Specific tests were carried out on the system in order to assess its performance. Futhermore we have measured some of the most important parameters of the system for PET application.

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El objetivo de este proyecto es diseñar un sistema capaz de controlar la velocidad de rotación de un motor DC en función del valor de temperatura obtenido de un sensor. Para ello se generará con un microcontrolador una señal PWM, cuyo ciclo de trabajo estará en función de la temperatura medida. En lo que respecta a la fase de diseño, hay dos partes claramente diferenciadas, relativas al hardware y al software. En cuanto al diseño del hardware puede hacerse a su vez una división en dos partes. En primer lugar, hubo que diseñar la circuitería necesaria para adaptar los niveles de tensión entregados por el sensor de temperatura a los niveles requeridos por ADC, requerido para digitalizar la información para su posterior procesamiento por parte del microcontrolador. Por tanto hubo que diseñar capaz de corregir el offset y la pendiente de la función tensión-temperatura del sensor, a fin de adaptarlo al rango de tensión requerido por el ADC. Por otro lado, hubo que diseñar el circuito encargado de controlar la velocidad de rotación del motor. Este circuito estará basado en un transistor MOSFET en conmutación, controlado mediante una señal PWM como se mencionó anteriormente. De esta manera, al variar el ciclo de trabajo de la señal PWM, variará de manera proporcional la tensión que cae en el motor, y por tanto su velocidad de rotación. En cuanto al diseño del software, se programó el microcontrolador para que generase una señal PWM en uno de sus pines en función del valor entregado por el ADC, a cuya entrada está conectada la tensión obtenida del circuito creado para adaptar la tensión generada por el sensor. Así mismo, se utiliza el microcontrolador para representar el valor de temperatura obtenido en una pantalla LCD. Para este proyecto se eligió una placa de desarrollo mbed, que incluye el microcontrolador integrado, debido a que facilita la tarea del prototipado. Posteriormente se procedió a la integración de ambas partes, y testeado del sistema para comprobar su correcto funcionamiento. Puesto que el resultado depende de la temperatura medida, fue necesario simular variaciones en ésta, para así comprobar los resultados obtenidos a distintas temperaturas. Para este propósito se empleó una bomba de aire caliente. Una vez comprobado el funcionamiento, como último paso se diseñó la placa de circuito impreso. Como conclusión, se consiguió desarrollar un sistema con un nivel de exactitud y precisión aceptable, en base a las limitaciones del sistema. SUMMARY: It is obvious that day by day people’s daily life depends more on technology and science. Tasks tend to be done automatically, making them simpler and as a result, user life is more comfortable. Every single task that can be controlled has an electronic system behind. In this project, a control system based on a microcontroller was designed for a fan, allowing it to go faster when temperature rises or slowing down as the environment gets colder. For this purpose, a microcontroller was programmed to generate a signal, to control the rotation speed of the fan depending on the data acquired from a temperature sensor. After testing the whole design developed in the laboratory, the next step taken was to build a prototype, which allows future improvements in the system that are discussed in the corresponding section of the thesis.

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We are investigating the performances of a data acquisition system for Time of Flight PET, based on LYSO crystal slabs and 64 channels Silicon Photomultipliers matrices (1.2 cm2 of active area each). Measurements have been performed to test the timing capability of the detection system (SiPM matices coupled to a LYSO slab and the read-out electronics) with both test signal and radioactive source.

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A basic requirement of the data acquisition systems used in long pulse fusion experiments is the real time physical events detection in signals. Developing such applications is usually a complex task, so it is necessary to develop a set of hardware and software tools that simplify their implementation. This type of applications can be implemented in ITER using fast controllers. ITER is standardizing the architectures to be used for fast controller implementation. Until now the standards chosen are PXIe architectures (based on PCIe) for the hardware and EPICS middleware for the software. This work presents the methodology for implementing data acquisition and pre-processing using FPGA-based DAQ cards and how to integrate these in fast controllers using EPICS.

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1. Canopies are complex multilayered structures comprising individual plant crowns exposing a multifaceted surface area to sunlight. Foliage arrangement and properties are the main mediators of canopy functions. The leaves act as light traps whose exposure to sunlight varies with time of the day, date and latitude in a trade-off between photosynthetic light harvesting and excessive or photoinhibitory light avoidance. To date, ecological research based upon leaf sampling has been limited by the available echnology, with which data acquisition becomes labour intensive and time-consuming, given the verwhelming number of leaves involved. 2. In the present study, our goal involved developing a tool capable of easuring a sufficient number of leaves to enable analysis of leaf populations, tree crowns and canopies.We specifically tested whether a cell phone working as a 3Dpointer could yield reliable, repeatable and valid leaf anglemeasurements with a simple gesture. We evaluated the accuracy of this method under controlled conditions, using a 3D digitizer, and we compared performance in the field with the methods commonly used. We presented an equation to estimate the potential proportion of the leaf exposed to direct sunlight (SAL) at any given time and compared the results with those obtained bymeans of a graphicalmethod. 3. We found a strong and highly significant correlation between the graphical methods and the equation presented. The calibration process showed a strong correlation between the results derived from the two methods with amean relative difference below 10%. Themean relative difference in calculation of instantaneous exposure was below 5%. Our device performed equally well in diverse locations, in which we characterized over 700 leaves in a single day. 4. The newmethod, involving the use of a cell phone, ismuchmore effective than the traditionalmethods or digitizers when the goal is to scale up from leaf position to performance of leaf populations, tree crowns or canopies. Our methodology constitutes an affordable and valuable tool within which to frame a wide range of ecological hypotheses and to support canopy modelling approaches.

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EPICS (Experimental Physics and Industrial Control System) lies in a set of software tools and applications which provide a software infrastructure for building distributed data acquisition and control systems. Currently there is an increase in use of such systems in large Physics experiments like ITER, ESS, and FREIA. In these experiments, advanced data acquisition systems using FPGA-based technology like FlexRIO are more frequently been used. The particular case of ITER (International Thermonuclear Experimental Reactor), the instrumentation and control system is supported by CCS (CODAC Core System), based on RHEL (Red Hat Enterprise Linux) operating system, and by the plant design specifications in which every CCS element is defined either hardware, firmware or software. In this degree final project the methodology proposed in Implementation of Intelligent Data Acquisition Systems for Fusion Experiments using EPICS and FlexRIO Technology Sanz et al. [1] is used. The final objective is to provide a document describing the fulfilled process and the source code of the data acquisition system accomplished. The use of the proposed methodology leads to have two diferent stages. The first one consists of the hardware modelling with graphic design tools like LabVIEWFPGA which later will be implemented in the FlexRIO device. In the next stage the design cycle is completed creating an EPICS controller that manages the device using a generic device support layer named NDS (Nominal Device Support). This layer integrates the data acquisition system developed into CCS (Control, data access and communication Core System) as an EPICS interface to the system. The use of FlexRIO technology drives the use of LabVIEW and LabVIEW FPGA respectively. RESUMEN. EPICS (Experimental Physics and Industrial Control System) es un conjunto de herramientas software utilizadas para el desarrollo e implementación de sistemas de adquisición de datos y control distribuidos. Cada vez es más utilizado para entornos de experimentación física a gran escala como ITER, ESS y FREIA entre otros. En estos experimentos se están empezando a utilizar sistemas de adquisición de datos avanzados que usan tecnología basada en FPGA como FlexRIO. En el caso particular de ITER, el sistema de instrumentación y control adoptado se basa en el uso de la herramienta CCS (CODAC Core System) basado en el sistema operativo RHEL (Red Hat) y en las especificaciones del diseño del sistema de planta, en la cual define todos los elementos integrantes del CCS, tanto software como firmware y hardware. En este proyecto utiliza la metodología propuesta para la implementación de sistemas de adquisición de datos inteligente basada en EPICS y FlexRIO. Se desea generar una serie de ejemplos que cubran dicho ciclo de diseño completo y que serían propuestos como casos de uso de dichas tecnologías. Se proporcionará un documento en el que se describa el trabajo realizado así como el código fuente del sistema de adquisición. La metodología adoptada consta de dos etapas diferenciadas. En la primera de ellas se modela el hardware y se sintetiza en el dispositivo FlexRIO utilizando LabVIEW FPGA. Posteriormente se completa el ciclo de diseño creando un controlador EPICS que maneja cada dispositivo creado utilizando una capa software genérica de manejo de dispositivos que se denomina NDS (Nominal Device Support). Esta capa integra la solución en CCS realizando la interfaz con la capa EPICS del sistema. El uso de la tecnología FlexRIO conlleva el uso del lenguaje de programación y descripción hardware LabVIEW y LabVIEW FPGA respectivamente.

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In the framework of the ITER Control Breakdown Structure (CBS), Plant System Instrumentation & Control (I&C) defines the hardware and software required to control one or more plant systems [1]. For diagnostics, most of the complex Plant System I&C are to be delivered by ITER Domestic Agencies (DAs). As an example for the DAs, ITER Organization (IO) has developed several use cases for diagnostics Plant System I&C that fully comply with guidelines presented in the Plant Control Design Handbook (PCDH) [2]. One such use case is for neutron diagnostics, specifically the Fission Chamber (FC), which is responsible for delivering time-resolved measurements of neutron source strength and fusion power to aid in assessing the functional performance of ITER [3]. ITER will deploy four Fission Chamber units, each consisting of three individual FC detectors. Two of these detectors contain Uranium 235 for Neutron detection, while a third "dummy" detector will provide gamma and noise detection. The neutron flux from each MFC is measured by the three methods: . Counting Mode: measures the number of individual pulses and their location in the record. Pulse parameters (threshold and width) are user configurable. . Campbelling Mode (Mean Square Voltage): measures the RMS deviation in signal amplitude from its average value. .Current Mode: integrates the signal amplitude over the measurement period

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Las herramientas de configuración basadas en lenguajes de alto nivel como LabVIEW permiten el desarrollo de sistemas de adquisición de datos basados en hardware reconfigurable FPGA muy complejos en un breve periodo de tiempo. La estandarización del ciclo de diseño hardware/software y la utilización de herramientas como EPICS facilita su integración con la plataforma de adquisición y control ITER CODAC CORE SYSTEM (CCS) basada en Linux. En este proyecto se propondrá una metodología que simplificará el ciclo completo de integración de plataformas novedosas, como cRIO, en las que el funcionamiento del hardware de adquisición puede ser modificado por el usuario para que éste se amolde a sus requisitos específicos. El objetivo principal de este proyecto fin de master es realizar la integración de un sistema cRIO NI9159 y diferentes módulos de E/S analógica y digital en EPICS y en CODAC CORE SYSTEM (CCS). Este último consiste en un conjunto de herramientas software que simplifican la integración de los sistemas de instrumentación y control del experimento ITER. Para cumplir el objetivo se realizarán las siguientes tareas: • Desarrollo de un sistema de adquisición de datos basado en FPGA con la plataforma hardware CompactRIO. En esta tarea se realizará la configuración del sistema y la implementación en LabVIEW para FPGA del hardware necesario para comunicarse con los módulos: NI9205, NI9264, NI9401.NI9477, NI9426, NI9425 y NI9476 • Implementación de un driver software utilizando la metodología de AsynDriver para integración del cRIO con EPICS. Esta tarea requiere definir todos los records necesarios que exige EPICS y crear las interfaces adecuadas que permitirán comunicarse con el hardware. • Implementar la descripción del sistema cRIO y del driver EPICS en el sistema de descripción de plantas de ITER llamado SDD. Esto automatiza la creación de las aplicaciones de EPICS que se denominan IOCs. SUMMARY The configuration tools based in high-level programing languages like LabVIEW allows the development of high complex data acquisition systems based on reconfigurable hardware FPGA in a short time period. The standardization of the hardware/software design cycle and the use of tools like EPICS ease the integration with the data acquisition and control platform of ITER, the CODAC Core System based on Linux. In this project a methodology is proposed in order to simplify the full integration cycle of new platforms like CompactRIO (cRIO), in which the data acquisition functionality can be reconfigured by the user to fits its concrete requirements. The main objective of this MSc final project is to develop the integration of a cRIO NI-9159 and its different analog and digital Input/Output modules with EPICS in a CCS. The CCS consists of a set of software tools that simplifies the integration of instrumentation and control systems in the International Thermonuclear Reactor (ITER) experiment. To achieve such goal the following tasks are carried out: • Development of a DAQ system based on FPGA using the cRIO hardware platform. This task comprehends the configuration of the system and the implementation of the mandatory hardware to communicate to the I/O adapter modules NI9205, NI9264, NI9401, NI9477, NI9426, NI9425 y NI9476 using LabVIEW for FPGA. • Implementation of a software driver using the asynDriver methodology to integrate such cRIO system with EPICS. This task requires the definition of the necessary EPICS records and the creation of the appropriate interfaces that allow the communication with the hardware. • Develop the cRIO system’s description and the EPICS driver in the ITER plant description tool named SDD. This development will automate the creation of EPICS applications, called IOCs.

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In a series of attempts to research and document relevant sloshing type phenomena, a series of experiments have been conducted. The aim of this paper is to describe the setup and data processing of such experiments. A sloshing tank is subjected to angular motion. As a result pressure registers are obtained at several locations, together with the motion data, torque and a collection of image and video information. The experimental rig and the data acquisition systems are described. Useful information for experimental sloshing research practitioners is provided. This information is related to the liquids used in the experiments, the dying techniques, tank building processes, synchronization of acquisition systems, etc. A new procedure for reconstructing experimental data, that takes into account experimental uncertainties, is presented. This procedure is based on a least squares spline approximation of the data. Based on a deterministic approach to the first sloshing wave impact event in a sloshing experiment, an uncertainty analysis procedure of the associated first pressure peak value is described.

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EURATOM/CIEMAT and Technical University of Madrid (UPM) have been involved in the development of a FPSC [1] (Fast Plant System Control) prototype for ITER, based on PXIe (PCI eXtensions for Instrumentation). One of the main focuses of this project has been data acquisition and all the related issues, including scientific data archiving. Additionally, a new data archiving solution has been developed to demonstrate the obtainable performances and possible bottlenecks of scientific data archiving in Fast Plant System Control. The presented system implements a fault tolerant architecture over a GEthernet network where FPSC data are reliably archived on remote, while remaining accessible to be redistributed, within the duration of a pulse. The storing service is supported by a clustering solution to guaranty scalability, so that FPSC management and configuration may be simplified, and a unique view of all archived data provided. All the involved components have been integrated under EPICS [2] (Experimental Physics and Industrial Control System), implementing in each case the necessary extensions, state machines and configuration process variables. The prototyped solution is based on the NetCDF-4 [3] and [4] (Network Common Data Format) file format in order to incorporate important features, such as scientific data models support, huge size files management, platform independent codification, or single-writer/multiple-readers concurrency. In this contribution, a complete description of the above mentioned solution is presented, together with the most relevant results of the tests performed, while focusing in the benefits and limitations of the applied technologies.

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The development of new-generation intelligent vehicle technologies will lead to a better level of road safety and CO2 emission reductions. However, the weak point of all these systems is their need for comprehensive and reliable data. For traffic data acquisition, two sources are currently available: 1) infrastructure sensors and 2) floating vehicles. The former consists of a set of fixed point detectors installed in the roads, and the latter consists of the use of mobile probe vehicles as mobile sensors. However, both systems still have some deficiencies. The infrastructure sensors retrieve information fromstatic points of the road, which are spaced, in some cases, kilometers apart. This means that the picture of the actual traffic situation is not a real one. This deficiency is corrected by floating cars, which retrieve dynamic information on the traffic situation. Unfortunately, the number of floating data vehicles currently available is too small and insufficient to give a complete picture of the road traffic. In this paper, we present a floating car data (FCD) augmentation system that combines information fromfloating data vehicles and infrastructure sensors, and that, by using neural networks, is capable of incrementing the amount of FCD with virtual information. This system has been implemented and tested on actual roads, and the results show little difference between the data supplied by the floating vehicles and the virtual vehicles.

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La mayoría de las aplicaciones forestales del escaneo laser aerotransportado (ALS, del inglés airborne laser scanning) requieren la integración y uso simultaneo de diversas fuentes de datos, con el propósito de conseguir diversos objetivos. Los proyectos basados en sensores remotos normalmente consisten en aumentar la escala de estudio progresivamente a lo largo de varias fases de fusión de datos: desde la información más detallada obtenida sobre un área limitada (la parcela de campo), hasta una respuesta general de la cubierta forestal detectada a distancia de forma más incierta pero cubriendo un área mucho más amplia (la extensión cubierta por el vuelo o el satélite). Todas las fuentes de datos necesitan en ultimo termino basarse en las tecnologías de sistemas de navegación global por satélite (GNSS, del inglés global navigation satellite systems), las cuales son especialmente erróneas al operar por debajo del dosel forestal. Otras etapas adicionales de procesamiento, como la ortorectificación, también pueden verse afectadas por la presencia de vegetación, deteriorando la exactitud de las coordenadas de referencia de las imágenes ópticas. Todos estos errores introducen ruido en los modelos, ya que los predictores se desplazan de la posición real donde se sitúa su variable respuesta. El grado por el que las estimaciones forestales se ven afectadas depende de la dispersión espacial de las variables involucradas, y también de la escala utilizada en cada caso. Esta tesis revisa las fuentes de error posicional que pueden afectar a los diversos datos de entrada involucrados en un proyecto de inventario forestal basado en teledetección ALS, y como las propiedades del dosel forestal en sí afecta a su magnitud, aconsejando en consecuencia métodos para su reducción. También se incluye una discusión sobre las formas más apropiadas de medir exactitud y precisión en cada caso, y como los errores de posicionamiento de hecho afectan a la calidad de las estimaciones, con vistas a una planificación eficiente de la adquisición de los datos. La optimización final en el posicionamiento GNSS y de la radiometría del sensor óptico permitió detectar la importancia de este ultimo en la predicción de la desidad relativa de un bosque monoespecífico de Pinus sylvestris L. ABSTRACT Most forestry applications of airborne laser scanning (ALS) require the integration and simultaneous use of various data sources, pursuing a variety of different objectives. Projects based on remotely-sensed data generally consist in upscaling data fusion stages: from the most detailed information obtained for a limited area (field plot) to a more uncertain forest response sensed over a larger extent (airborne and satellite swath). All data sources ultimately rely on global navigation satellite systems (GNSS), which are especially error-prone when operating under forest canopies. Other additional processing stages, such as orthorectification, may as well be affected by vegetation, hence deteriorating the accuracy of optical imagery’s reference coordinates. These errors introduce noise to the models, as predictors displace from their corresponding response. The degree to which forest estimations are affected depends on the spatial dispersion of the variables involved and the scale used. This thesis reviews the sources of positioning errors which may affect the different inputs involved in an ALS-assisted forest inventory project, and how the properties of the forest canopy itself affects their magnitude, advising on methods for diminishing them. It is also discussed how accuracy should be assessed, and how positioning errors actually affect forest estimation, toward a cost-efficient planning for data acquisition. The final optimization in positioning the GNSS and optical image allowed to detect the importance of the latter in predicting relative density in a monospecific Pinus sylvestris L. forest.

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The electrical power distribution and commercialization scenario is evolving worldwide, and electricity companies, faced with the challenge of new information requirements, are demanding IT solutions to deal with the smart monitoring of power networks. Two main challenges arise from data management and smart monitoring of power networks: real-time data acquisition and big data processing over short time periods. We present a solution in the form of a system architecture that conveys real time issues and has the capacity for big data management.

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Current fusion devices consist of multiple diagnostics and hundreds or even thousands of signals. This situation forces on multiple occasions to use distributed data acquisition systems as the best approach. In this type of distributed systems, one of the most important issues is the synchronization between signals, so that it is possible to have a temporal correlation as accurate as possible between the acquired samples of all channels. In last decades, many fusion devices use different types of video cameras to provide inside views of the vessel during operations and to monitor plasma behavior. The synchronization between each video frame and the rest of the different signals acquired from any other diagnostics is essential in order to know correctly the plasma evolution, since it is possible to analyze jointly all the information having accurate knowledge of their temporal correlation. The developed system described in this paper allows timestamping image frames in a real-time acquisition and processing system using 1588 clock distribution. The system has been implemented using FPGA based devices together with a 1588 synchronized timing card (see Fig.1). The solution is based on a previous system [1] that allows image acquisition and real-time image processing based on PXIe technology. This architecture is fully compatible with the ITER Fast Controllers [2] and offers integration with EPICS to control and monitor the entire system. However, this set-up is not able to timestamp the frames acquired since the frame grabber module does not present any type of timing input (IRIG-B, GPS, PTP). To solve this lack, an IEEE1588 PXI timing device its used to provide an accurate way to synchronize distributed data acquisition systems using the Precision Time Protocol (PTP) IEEE 1588 2008 standard. This local timing device can be connected to a master clock device for global synchronization. The timing device has a buffer timestamp for each PXI trigger line and requires tha- a software application assigns each frame the corresponding timestamp. The previous action is critical and cannot be achieved if the frame rate is high. To solve this problem, it has been designed a solution that distributes the clock from the IEEE 1588 timing card to all FlexRIO devices [3]. This solution uses two PXI trigger lines that provide the capacity to assign timestamps to every frame acquired and register events by hardware in a deterministic way. The system provides a solution for timestamping frames to synchronize them with the rest of the different signals.

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Embedded context management in resource-constrained devices (e.g. mobile phones, autonomous sensors or smart objects) imposes special requirements in terms of lightness for data modelling and reasoning. In this paper, we explore the state-of-the-art on data representation and reasoning tools for embedded mobile reasoning and propose a light inference system (LIS) aiming at simplifying embedded inference processes offering a set of functionalities to avoid redundancy in context management operations. The system is part of a service-oriented mobile software framework, conceived to facilitate the creation of context-aware applications—it decouples sensor data acquisition and context processing from the application logic. LIS, composed of several modules, encapsulates existing lightweight tools for ontology data management and rule-based reasoning, and it is ready to run on Java-enabled handheld devices. Data management and reasoning processes are designed to handle a general ontology that enables communication among framework components. Both the applications running on top of the framework and the framework components themselves can configure the rule and query sets in order to retrieve the information they need from LIS. In order to test LIS features in a real application scenario, an ‘Activity Monitor’ has been designed and implemented: a personal health-persuasive application that provides feedback on the user’s lifestyle, combining data from physical and virtual sensors. In this case of use, LIS is used to timely evaluate the user’s activity level, to decide on the convenience of triggering notifications and to determine the best interface or channel to deliver these context-aware alerts.d