111 resultados para Sensores infravermelhos
Resumo:
A Wireless Sensor Network (WSN) consists of distributed devices in an area in order to monitor physical variables such as temperature, pressure, vibration, motion and environmental conditions in places where wired networks would be difficult or impractical to implement, for example, industrial applications of difficult access, monitoring and control of oil wells on-shore or off-shore, monitoring of large areas of agricultural and animal farming, among others. To be viable, a WSN should have important requirements such as low cost, low latency, and especially low power consumption. However, to ensure these requirements, these networks suffer from limited resources, and eventually being used in hostile environments, leading to high failure rates, such as segmented routing, mes sage loss, reducing efficiency, and compromising the entire network, inclusive. This work aims to present the FTE-LEACH, a fault tolerant and energy efficient routing protocol that maintains efficiency in communication and dissemination of data.This protocol was developed based on the IEEE 802.15.4 standard and suitable for industrial networks with limited energy resources
Resumo:
Cryptography is the main form to obtain security in any network. Even in networks with great energy consumption restrictions, processing and memory limitations, as the Wireless Sensors Networks (WSN), this is no different. Aiming to improve the cryptography performance, security and the lifetime of these networks, we propose a new cryptographic algorithm developed through the Genetic Programming (GP) techniques. For the development of the cryptographic algorithm’s fitness criteria, established by the genetic GP, nine new cryptographic algorithms were tested: AES, Blowfish, DES, RC6, Skipjack, Twofish, T-DES, XTEA and XXTEA. Starting from these tests, fitness functions was build taking into account the execution time, occupied memory space, maximum deviation, irregular deviation and correlation coefficient. After obtaining the genetic GP, the CRYSEED and CRYSEED2 was created, algorithms for the 8-bits devices, optimized for WSNs, i.e., with low complexity, few memory consumption and good security for sensing and instrumentation applications.
Resumo:
Cryptography is the main form to obtain security in any network. Even in networks with great energy consumption restrictions, processing and memory limitations, as the Wireless Sensors Networks (WSN), this is no different. Aiming to improve the cryptography performance, security and the lifetime of these networks, we propose a new cryptographic algorithm developed through the Genetic Programming (GP) techniques. For the development of the cryptographic algorithm’s fitness criteria, established by the genetic GP, nine new cryptographic algorithms were tested: AES, Blowfish, DES, RC6, Skipjack, Twofish, T-DES, XTEA and XXTEA. Starting from these tests, fitness functions was build taking into account the execution time, occupied memory space, maximum deviation, irregular deviation and correlation coefficient. After obtaining the genetic GP, the CRYSEED and CRYSEED2 was created, algorithms for the 8-bits devices, optimized for WSNs, i.e., with low complexity, few memory consumption and good security for sensing and instrumentation applications.
Resumo:
The Wireless Sensor Networks (WSN) methods applied to the lifting of oil present as an area with growing demand technical and scientific in view of the optimizations that can be carried forward with existing processes. This dissertation has as main objective to present the development of embedded systems dedicated to a wireless sensor network based on IEEE 802.15.4, which applies the ZigBee protocol, between sensors, actuators and the PLC (Programmable Logic Controller), aiming to solve the present problems in the deployment and maintenance of the physical communication of current elevation oil units based on the method Plunger-Lift. Embedded systems developed for this application will be responsible for acquiring information from sensors and control actuators of the devices present at the well, and also, using the Modbus protocol to make this network becomes transparent to the PLC responsible for controlling the production and delivery information for supervisory SISAL
Resumo:
Originally aimed at operational objectives, the continuous measurement of well bottomhole pressure and temperature, recorded by permanent downhole gauges (PDG), finds vast applicability in reservoir management. It contributes for the monitoring of well performance and makes it possible to estimate reservoir parameters on the long term. However, notwithstanding its unquestionable value, data from PDG is characterized by a large noise content. Moreover, the presence of outliers within valid signal measurements seems to be a major problem as well. In this work, the initial treatment of PDG signals is addressed, based on curve smoothing, self-organizing maps and the discrete wavelet transform. Additionally, a system based on the coupling of fuzzy clustering with feed-forward neural networks is proposed for transient detection. The obtained results were considered quite satisfactory for offshore wells and matched real requisites for utilization
Resumo:
BRITTO, Ricardo S.; MEDEIROS, Adelardo A. D.; ALSINA, Pablo J. Uma arquitetura distribuída de hardware e software para controle de um robô móvel autônomo. In: SIMPÓSIO BRASILEIRO DE AUTOMAÇÃO INTELIGENTE,8., 2007, Florianópolis. Anais... Florianópolis: SBAI, 2007.
Resumo:
SOUZA, Anderson A.S. ; MEDEIROS, Adelardo A. D. ; GONÇALVES, Luiz Marcos G. . Algorítmo de mapeamento usando modelagem probabilística. In: SIMPOSIO BRASILEIRO DE AUTOMAÇÃO INTELIGENTE, 2007, Natal. Anais... Natal, 2007.
Resumo:
Nickel-based catalysts supported on alumina have been widely used in various reactions to obtain synthesis gas or hydrogen. Usually, higher conversion levels are obtained by these catalysts, however, the deactivation by coke formation and sintering of metal particles are still problems to be solved. Several approaches have been employed in order to minimize these problems, among which stands out in recent years the use of additives such as oxides of alkali metals and rare earths. Similarly, the use of methodologies for the synthesis faster, easier, applicable on an industrial scale and to allow control of the microstructural characteristics of these catalysts, can together provide the solution to this problem. In this work, oxides with spinel type structure AB2O4, where A represents divalent cation and B represents trivalent cations are an important class of ceramic materials investigated worldwide in different fields of applications. The nickel cobaltite (NiCo2O4) was oxides of spinel type which has attracted considerable interest due to its applicability in several areas, such as chemical sensors, flat panel displays, optical limiters, electrode materials, pigments, electrocatalysis, electronic ceramics, among others. The catalyst precursor NiCo2O4 was prepared by a new chemical synthesis route using gelatine as directing agent. The polymer resin obtained was calcined at 350°C. The samples were calcined at different temperatures (550, 750 and 950°C) and characterized by X ray diffraction, measurements of specific surface area, temperature programmed reduction and scanning electron microscopy. The materials heat treated at 550 and 750°C were tested in the partial oxidation of methane. The set of techniques revealed, for solid preparations, the presence of the phase of spinel-type structure with the NiCo2O4 NixCo1-xO solid solution. This solid solution was identified by Rietveld refinement at all temperatures of heat treatment. The catalyst precursors calcined at 550 and 750°C showed conversion levels around 25 and 75%, respectively. The reason H2/CO was around 2 to the precursor treated at 750°C, proposed reason for the reaction of partial oxidation of methane, one can conclude that this material can be shown to produce synthesis gas suitable for use in the synthesis Fischer-Tropsch process
Resumo:
The development and study of detectors sensitive to flammable combustible and toxic gases at low cost is a crucial technology challenge to enable marketable versions to the market in general. Solid state sensors are attractive for commercial purposes by the strength and lifetime, because it isn t consumed in the reaction with the gas. In parallel, the use of synthesis techniques more viable for the applicability on an industrial scale are more attractive to produce commercial products. In this context ceramics with spinel structure were obtained by microwave-assisted combustion for application to flammable fuel gas detectors. Additionally, alternatives organic-reducers were employed to study the influence of those in the synthesis process and the differences in performance and properties of the powders obtained. The organic- reducers were characterized by Thermogravimetry (TG) and Derivative Thermogravimetry (DTG). After synthesis, the samples were heat treated and characterized by Fourier Transform Infrared Spectroscopy (FTIR), X-ray Diffraction (XRD), analysis by specific area by BET Method and Scanning Electron Microscopy (SEM). Quantification of phases and structural parameters were carried through Rietveld method. The methodology was effective to obtain Ni-Mn mixed oxides. The fuels influenced in obtaining spinel phase and morphology of the samples, however samples calcined at 950 °C there is just the spinel phase in the material regardless of the organic-reducer. Therefore, differences in performance are expected in technological applications when sample equal in phase but with different morphologies are tested
Resumo:
Continuous Synthesis by Solution Combustion was employed in this work aiming to obtain tin dioxide nanostructured. Basically, a precursor solution is prepared and then be atomized and sprayed into the flame, where its combustion occurs, leading to the formation of particles. This is a recent technique that shows an enormous potential in oxides deposition, mainly by the low cost of equipment and precursors employed. The tin dioxide (SnO2) nanostructured has been widely used in various applications, especially as gas sensors and varistors. In the case of sensors based on semiconducting ceramics, where surface reactions are responsible for the detection of gases, the importance of surface area and particle size is even greater. The preference for a nanostructured material is based on its significant increase in surface area compared to conventional microcrystalline powders and small particle size, which may benefit certain properties such as high electrical conductivity, high thermal stability, mechanical and chemical. In this work, were employed as precursor solution tin chloride dehydrate diluted in anhydrous ethyl alcohol. Were utilized molar ratio chloride/solvent of 0,75 with the purpose of investigate its influence in the microstructure of produced powder. The solution precursor flux was 3 mL/min. Analysis with X-ray diffraction appointed that a solution precursor with molar ratio chloride/solvent of 0,75 leads to crystalline powder with single phase and all peaks are attributed to phase SnO2. Parameters as distance from the flame with atomizer distance from the capture system with the pilot, molar ratio and solution flux doesn t affect the presence of tin dioxide in the produced powder. In the characterization of the obtained powder techniques were used as thermogravimetric (TGA) and thermodiferential analysis (DTA), particle size by laser diffraction (GDL), crystallographic analysis by X-ray diffraction (XRD), morphology by scanning electron microscopy (SEM), transmission electron microscopy (TEM), specific surface area (BET) and electrical conductivity analysis. The techniques used revealed that the SnO2 exhibits behavior of a semiconductor material, and a potentially promising material for application as varistor and sensor systems for gas
Resumo:
Polymer matrix composites offer advantages for many applications due their combination of properties, which includes low density, high specific strength and modulus of elasticity and corrosion resistance. However, the application of non-destructive techniques using magnetic sensors for the evaluation these materials is not possible since the materials are non-magnetizable. Ferrites are materials with excellent magnetic properties, chemical stability and corrosion resistance. Due to these properties, these materials are promising for the development of polymer composites with magnetic properties. In this work, glass fiber / epoxy circular plates were produced with 10 wt% of cobalt or barium ferrite particles. The cobalt ferrite was synthesized by the Pechini method. The commercial barium ferrite was subjected to a milling process to study the effect of particle size on the magnetic properties of the material. The characterization of the ferrites was carried out by x-ray diffraction (XRD), field emission gun scanning electron microscopy (FEG-SEM) and vibrating sample magnetometry (VSM). Circular notches of 1, 5 and 10 mm diameter were introduced in the composite plates using a drill bit for the non-destructive evaluation by the technique of magnetic flux leakage (MFL). The results indicated that the magnetic signals measured in plates with barium ferrite without milling and cobalt ferrite showed good correlation with the presence of notches. The milling process for 12 h and 20 h did not contribute to improve the identification of smaller size notches (1 mm). However, the smaller particle size produced smoother magnetic curves, with fewer discontinuities and improved signal-to-noise ratio. In summary, the results suggest that the proposed approach has great potential for the detection of damage in polymer composites structures
Resumo:
With the advances in medicine, life expectancy of the world population has grown considerably in recent decades. Studies have been performed in order to maintain the quality of life through the development of new drugs and new surgical procedures. Biomaterials is an example of the researches to improve quality of life, and its use goes from the reconstruction of tissues and organs affected by diseases or other types of failure, to use in drug delivery system able to prolong the drug in the body and increase its bioavailability. Biopolymers are a class of biomaterials widely targeted by researchers since they have ideal properties for biomedical applications, such as high biocompatibility and biodegradability. Poly (lactic acid) (PLA) is a biopolymer used as a biomaterial and its monomer, lactic acid, is eliminated by the Krebs Cycle (citric acid cycle). It is possible to synthesize PLA through various synthesis routes, however, the direct polycondensation is cheaper due the use of few steps of polymerization. In this work we used experimental design (DOE) to produce PLAs with different molecular weight from the direct polycondensation of lactic acid, with characteristics suitable for use in drug delivery system (DDS). Through the experimental design it was noted that the time of esterification, in the direct polycondensation, is the most important stage to obtain a higher molecular weight. The Fourier Transform Infrared (FTIR) spectrograms obtained were equivalent to the PLAs available in the literature. Results of Differential Scanning Calorimetry (DSC) showed that all PLAs produced are semicrystalline with glass transition temperatures (Tgs) ranging between 36 - 48 °C, and melting temperatures (Tm) ranging from 117 to 130 °C. The PLAs molecular weight characterized from Size Exclusion Chromatography (SEC), varied from 1000 to 11,000 g/mol. PLAs obtained showed a fibrous morphology characterized by Scanning Electron Microscopy (SEM)
Resumo:
This master dissertation presents the study and implementation of inteligent algorithms to monitor the measurement of sensors involved in natural gas custody transfer processes. To create these algoritmhs Artificial Neural Networks are investigated because they have some particular properties, such as: learning, adaptation, prediction. A neural predictor is developed to reproduce the sensor output dynamic behavior, in such a way that its output is compared to the real sensor output. A recurrent neural network is used for this purpose, because of its ability to deal with dynamic information. The real sensor output and the estimated predictor output work as the basis for the creation of possible sensor fault detection and diagnosis strategies. Two competitive neural network architectures are investigated and their capabilities are used to classify different kinds of faults. The prediction algorithm and the fault detection classification strategies, as well as the obtained results, are presented
Resumo:
The thermoelectric energy conversion can be performed directly on generators without moving parts, using the principle of SEEBECK effect, obtained in junctions of drivers' thermocouples and most recently in semiconductor junctions type p-n which have increased efficiency of conversion. When termogenerators are exposed to the temperature difference (thermal gradient) eletromotriz a force is generated inducing the appearance of an electric current in the circuit. Thus, it is possible to convert the heat of combustion of a gas through a burner in power, being a thermoelectric generator. The development of infrared burners, using porous ceramic plate, is possible to improve the efficiency of heating, and reduce harmful emissions such as CO, CO2, NOx, etc.. In recent years the meliorate of thermoelectric modules semiconductor (TEG's) has stimulated the development of devices generating and recovery of thermal irreversibility of thermal machines and processes, improving energy efficiency and exergy these systems, especially processes that enable the cogeneration of energy. This work is based on the construction and evaluation of a prototype in a pilot scale, for energy generation to specific applications. The unit uses a fuel gas (LPG) as a primary energy source. The prototype consists of a porous plate burner infrared, an adapter to the module generator, a set of semiconductor modules purchased from Hi-Z Inc. and a heat exchanger to be used as cold source. The prototype was mounted on a test bench, using a system of acquisition of temperature, a system of application of load and instrumentation to assess its functioning and performance. The prototype had an efficiency of chemical conversion of 0.31% for electrical and heat recovery for cogeneration of about 33.2%, resulting in an overall efficiency of 33.51%. The efficiency of energy exergy next shows that the use of primary energy to useful fuel was satisfactory, although the proposed mechanism has also has a low performance due to underuse of the area heated by the small number of modules, as well as a thermal gradient below the ideal informed by the manufacturer, and other factors. The test methodology adopted proved to be suitable for evaluating the prototype
Resumo:
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