18 resultados para Digital signal processor

em Universidade Federal do Rio Grande do Norte(UFRN)


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This work deals with the development of an experimental study on a power supply of high frequency that provides the toch plasmica to be implemented in PLASPETRO project, which consists of two static converters developed by using Insulated Gate Bipolar Transistor (IGBT). The drivers used to control these keys are triggered by Digital Signal Processor (DSP) through optical fibers to reduce problems with electromagnetic interference (EMI). The first stage consists of a pre-regulator in the form of an AC to DC converter with three-phase boost power factor correction which is the main theme of this work, while the second is the source of high frequency itself. A series-resonant inverter consists of four (4) cell inverters operating in a frequency around 115 kHz each one in soft switching mode, alternating itself to supply the load (plasma torch) an alternating current with a frequency of 450 kHz. The first stage has the function of providing the series-resonant inverter a DC voltage, with the value controlled from the power supply provided by the electrical system of the utility, and correct the power factor of the system as a whole. This level of DC bus voltage at the output of the first stage will be used to control the power transferred by the inverter to the load, and it may vary from 550 VDC to a maximum of 800 VDC. To control the voltage level of DC bus driver used a proportional integral (PI) controller and to achieve the unity power factor it was used two other proportional integral currents controllers. Computational simulations were performed to assist in sizing and forecasting performance. All the control and communications needed to stage supervisory were implemented on a DSP

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The transport of fluids through pipes is used in the oil industry, being the pipelines an important link in the logistics flow of fluids. However, the pipelines suffer deterioration in their walls caused by several factors which may cause loss of fluids to the environment, justifying the investment in techniques and methods of leak detection to minimize fluid loss and environmental damage. This work presents the development of a supervisory module in order to inform to the operator the leakage in the pipeline monitored in the shortest time possible, in order that the operator log procedure that entails the end of the leak. This module is a component of a system designed to detect leaks in oil pipelines using sonic technology, wavelets and neural networks. The plant used in the development and testing of the module presented here was the system of tanks of LAMP, and its LAN, as monitoring network. The proposal consists of, basically, two stages. Initially, assess the performance of the communication infrastructure of the supervisory module. Later, simulate leaks so that the DSP sends information to the supervisory performs the calculation of the location of leaks and indicate to which sensor the leak is closer, and using the system of tanks of LAMP, capture the pressure in the pipeline monitored by piezoresistive sensors, this information being processed by the DSP and sent to the supervisory to be presented to the user in real time

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Embedded systems are widely spread nowadays. An example is the Digital Signal Processor (DSP), which is a high processing power device. This work s contribution consist of exposing DSP implementation of the system logic for detecting leaks in real time. Among the various methods of leak detection available today this work uses a technique based on the pipe pressure analysis and usesWavelet Transform and Neural Networks. In this context, the DSP, in addition to do the pressure signal digital processing, also communicates to a Global Positioning System (GPS), which helps in situating the leak, and to a SCADA, sharing information. To ensure robustness and reliability in communication between DSP and SCADA the Modbus protocol is used. As it is a real time application, special attention is given to the response time of each of the tasks performed by the DSP. Tests and leak simulations were performed using the structure of Laboratory of Evaluation of Measurement in Oil (LAMP), at Federal University of Rio Grande do Norte (UFRN)

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Relevant researches have been growing on electric machine without mancal or bearing and that is generally named bearingless motor or specifically, mancal motor. In this paper it is made an introductory presentation about bearingless motor and its peripherical devices with focus on the design and implementation of sensors and interfaces needed to control rotor radial positioning and rotation of the machine. The signals from the machine are conditioned in analogic inputs of DSP TMS320F2812 and used in the control program. This work has a purpose to elaborate and build a system with sensors and interfaces suitable to the input and output of DSP TMS320F2812 to control a mancal motor, bearing in mind the modularity, simplicity of circuits, low number of power used, good noise imunity and good response frequency over 10 kHz. The system is tested at a modified ordinary induction motor of 3,7 kVA to be used with a bearingless motor with divided coil

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Electrical Motors transform electrical energy into mechanic energy in a relatively easy way. In some specific applications, there is a need for electrical motors to function with noncontaminated fluids, in high speed systems, under inhospitable conditions, or yet, in local of difficult access and considerable depth. In these cases, the motors with mechanical bearings are not adequate as their wear give rise to maintenance. A possible solution for these problems stems from two different alternatives: motors with magnetic bearings, that increase the length of the machine (not convenient), and the bearingless motors that aggregate compactness. Induction motors have been used more and more in research, as they confer more robustness to bearingless motors compared to other types of machines building with others motors. The research that has already been carried out with bearingless induction motors utilized prototypes that had their structures of stator/rotor modified, that differ most of the times from the conventional induction motors. The goal of this work is to study the viability of the use of conventional induction Motors for the beringless motors applications, pointing out the types of Motors of this category that can be more useful. The study uses the Finite Elements Method (FEM). As a means of validation, a conventional induction motor with squirrel-cage rotor was successfully used for the beringless motor application of the divided winding type, confirming the proposed thesis. The controlling system was implemented in a Digital Signal Processor (DSP)

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This work considers the development of a filtering system composed of an intelligent algorithm, that separates information and noise coming from sensors interconnected by Foundation Fieldbus (FF) network. The algorithm implementation will be made through FF standard function blocks, with on-line training through OPC (OLE for Process Control), and embedded technology in a DSP (Digital Signal Processor) that interacts with the fieldbus devices. The technique ICA (Independent Component Analysis), that explores the possibility of separating mixed signals based on the fact that they are statistically independent, was chosen to this Blind Source Separation (BSS) process. The algorithm and its implementations will be Presented, as well as the results

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The transport of fluids through pipes is used in the oil industry, being the pipelines an important link in the logistics flow of fluids. However, the pipelines suffer deterioration in their walls caused by several factors which may cause loss of fluids to the environment, justifying the investment in techniques and methods of leak detection to minimize fluid loss and environmental damage. This work presents the development of a supervisory module in order to inform to the operator the leakage in the pipeline monitored in the shortest time possible, in order that the operator log procedure that entails the end of the leak. This module is a component of a system designed to detect leaks in oil pipelines using sonic technology, wavelets and neural networks. The plant used in the development and testing of the module presented here was the system of tanks of LAMP, and its LAN, as monitoring network. The proposal consists of, basically, two stages. Initially, assess the performance of the communication infrastructure of the supervisory module. Later, simulate leaks so that the DSP sends information to the supervisory performs the calculation of the location of leaks and indicate to which sensor the leak is closer, and using the system of tanks of LAMP, capture the pressure in the pipeline monitored by piezoresistive sensors, this information being processed by the DSP and sent to the supervisory to be presented to the user in real time

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This work deals with a mathematical fundament for digital signal processing under point view of interval mathematics. Intend treat the open problem of precision and repesention of data in digital systems, with a intertval version of signals representation. Signals processing is a rich and complex area, therefore, this work makes a cutting with focus in systems linear invariant in the time. A vast literature in the area exists, but, some concepts in interval mathematics need to be redefined or to be elaborated for the construction of a solid theory of interval signal processing. We will construct a basic fundaments for signal processing in the interval version, such as basic properties linearity, stability, causality, a version to intervalar of linear systems e its properties. They will be presented interval versions of the convolution and the Z-transform. Will be made analysis of convergences of systems using interval Z-transform , a essentially interval distance, interval complex numbers , application in a interval filter.

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Post dispatch analysis of signals obtained from digital disturbances registers provide important information to identify and classify disturbances in systems, looking for a more efficient management of the supply. In order to enhance the task of identifying and classifying the disturbances - providing an automatic assessment - techniques of digital signal processing can be helpful. The Wavelet Transform has become a very efficient tool for the analysis of voltage or current signals, obtained immediately after disturbance s occurrences in the network. This work presents a methodology based on the Discrete Wavelet Transform to implement this process. It uses a comparison between distribution curves of signals energy, with and without disturbance. This is done for different resolution levels of its decomposition in order to obtain descriptors that permit its classification, using artificial neural networks

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The human voice is an important communication tool and any disorder of the voice can have profound implications for social and professional life of an individual. Techniques of digital signal processing have been used by acoustic analysis of vocal disorders caused by pathologies in the larynx, due to its simplicity and noninvasive nature. This work deals with the acoustic analysis of voice signals affected by pathologies in the larynx, specifically, edema, and nodules on the vocal folds. The purpose of this work is to develop a classification system of voices to help pre-diagnosis of pathologies in the larynx, as well as monitoring pharmacological treatments and after surgery. Linear Prediction Coefficients (LPC), Mel Frequency cepstral coefficients (MFCC) and the coefficients obtained through the Wavelet Packet Transform (WPT) are applied to extract relevant characteristics of the voice signal. For the classification task is used the Support Vector Machine (SVM), which aims to build optimal hyperplanes that maximize the margin of separation between the classes involved. The hyperplane generated is determined by the support vectors, which are subsets of points in these classes. According to the database used in this work, the results showed a good performance, with a hit rate of 98.46% for classification of normal and pathological voices in general, and 98.75% in the classification of diseases together: edema and nodules

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In this work we use Interval Mathematics to establish interval counterparts for the main tools used in digital signal processing. More specifically, the approach developed here is oriented to signals, systems, sampling, quantization, coding and Fourier transforms. A detailed study for some interval arithmetics which handle with complex numbers is provided; they are: complex interval arithmetic (or rectangular), circular complex arithmetic, and interval arithmetic for polar sectors. This lead us to investigate some properties that are relevant for the development of a theory of interval digital signal processing. It is shown that the sets IR and R(C) endowed with any correct arithmetic is not an algebraic field, meaning that those sets do not behave like real and complex numbers. An alternative to the notion of interval complex width is also provided and the Kulisch- Miranker order is used in order to write complex numbers in the interval form enabling operations on endpoints. The use of interval signals and systems is possible thanks to the representation of complex values into floating point systems. That is, if a number x 2 R is not representable in a floating point system F then it is mapped to an interval [x;x], such that x is the largest number in F which is smaller than x and x is the smallest one in F which is greater than x. This interval representation is the starting point for definitions like interval signals and systems which take real or complex values. It provides the extension for notions like: causality, stability, time invariance, homogeneity, additivity and linearity to interval systems. The process of quantization is extended to its interval counterpart. Thereafter the interval versions for: quantization levels, quantization error and encoded signal are provided. It is shown that the interval levels of quantization represent complex quantization levels and the classical quantization error ranges over the interval quantization error. An estimation for the interval quantization error and an interval version for Z-transform (and hence Fourier transform) is provided. Finally, the results of an Matlab implementation is given

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Digital signal processing (DSP) aims to extract specific information from digital signals. Digital signals are, by definition, physical quantities represented by a sequence of discrete values and from these sequences it is possible to extract and analyze the desired information. The unevenly sampled data can not be properly analyzed using standard techniques of digital signal processing. This work aimed to adapt a technique of DSP, the multiresolution analysis, to analyze unevenly smapled data, to aid the studies in the CoRoT laboratory at UFRN. The process is based on re-indexing the wavelet transform to handle unevenly sampled data properly. The was efective presenting satisfactory results

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In February 2011, the National Agency of Petroleum, Natural Gas and Biofuels (ANP) has published a new Technical Rules for Handling Land Pipeline Petroleum and Natural Gas Derivatives (RTDT). Among other things, the RTDT made compulsory the use of monitoring systems and leak detection in all onshore pipelines in the country. This document provides a study on the method for detection of transient pressure. The study was conducted on a industrial duct 16" diameter and 9.8 km long. The pipeline is fully pressurized and carries a multiphase mixture of crude oil, water and natural gas. For the study, was built an infrastructure for data acquisition and validation of detection algorithms. The system was designed with SCADA architecture. Piezoresistive sensors were installed at the ends of the duct and Digital Signal Processors (DSPs) were used for sampling, storage and processing of data. The study was based on simulations of leaks through valves and search for patterns that characterize the occurrence of such phenomena

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Neste trabalho, um controlador adaptativo backstepping a estrutura variável (Variable Structure Adaptive Backstepping Controller, VS-ABC) é apresentado para plantas monovariáveis, lineares e invariantes no tempo com grau relativo unitário. Ao invés das tradicionais leis integrais para estimação dos parâmetros da planta, leis chaveadas são utilizadas com o objetivo de aumentar a robustez em relação a incertezas paramétricas e distúrbios externos, bem como melhorar o desempenho transitório do sistema. Adicionalmente, o projeto do novo controlador é mais intuitivo quando comparado ao controlador backstepping original, uma vez que os relés introduzidos apresentam amplitudes diretamente relacionadas com os parâmetros nominais da planta. Esta nova abordagem, com uso de estrutura variável, também reduz a complexidade das implementações práticas, motivando a utilização de componentes industriais, tais como, FPGAs (Field Programmable Gate Arrays ), MCUs (Microcontrollers) e DSPs (Digital Signal Processors). Simulações preliminares para um sistema instável de primeira e segunda ordem são apresentadas de modo a corroborar os estudos. Um dos exemplos de Rohrs é ainda abordado através de simulações, para os dois cenários adaptativos: o controlador backstepping adaptativo original e o VS-ABC

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The use of Multiple Input Multiple Output (MIMO) systems has permitted the recent evolution of wireless communication standards. The Spatial Multiplexing MIMO technique, in particular, provides a linear gain at the transmission capacity with the minimum between the numbers of transmit and receive antennas. To obtain a near capacity performance in SM-MIMO systems a soft decision Maximum A Posteriori Probability MIMO detector is necessary. However, such detector is too complex for practical solutions. Hence, the goal of a MIMO detector algorithm aimed for implementation is to get a good approximation of the ideal detector while keeping an acceptable complexity. Moreover, the algorithm needs to be mapped to a VLSI architecture with small area and high data rate. Since Spatial Multiplexing is a recent technique, it is argued that there is still much room for development of related algorithms and architectures. Therefore, this thesis focused on the study of sub optimum algorithms and VLSI architectures for broadband MIMO detector with soft decision. As a result, novel algorithms have been developed starting from proposals of optimizations for already established algorithms. Based on these results, new MIMO detector architectures with configurable modulation and competitive area, performance and data rate parameters are here proposed. The developed algorithms have been extensively simulated and the architectures were synthesized so that the results can serve as a reference for other works in the area