Uma metodologia para modelagem e avaliação da dependabilidade de redes industriais sem fio

Ensuring the dependability requirements is essential for the industrial applications since faults may cause failures whose consequences result in economic losses, environmental damage or hurting people. Therefore, faced from the relevance of topic, this thesis proposes a methodology for the dependability evaluation of industrial wireless networks (WirelessHART, ISA100.11a, WIA-PA) on early design phase. However, the proposal can be easily adapted to maintenance and expansion stages of network. The proposal uses graph theory and fault tree formalism to create automatically an analytical model from a given wireless industrial network topology, where the dependability can be evaluated. The evaluation metrics supported are the reliability, availability, MTTF (mean time to failure), importance measures of devices, redundancy aspects and common cause failures. It must be emphasized that the proposal is independent of any tool to evaluate quantitatively the target metrics. However, due to validation issues it was used a tool widely accepted on academy for this purpose (SHARPE). In addition, an algorithm to generate the minimal cut sets, originally applied on graph theory, was adapted to fault tree formalism to guarantee the scalability of methodology in wireless industrial network environments (< 100 devices). Finally, the proposed methodology was validate from typical scenarios found in industrial environments, as star, line, cluster and mesh topologies. It was also evaluated scenarios with common cause failures and best practices to guide the design of an industrial wireless network. For guarantee scalability requirements, it was analyzed the performance of methodology in different scenarios where the results shown the applicability of proposal for networks typically found in industrial environments

Antenas de microfita com patch quase-fractal para aplicações em Redes WPAN/WLAN

The microstrip antennas are in constant evidence in current researches due to several advantages that it presents. Fractal geometry coupled with good performance and convenience of the planar structures are an excellent combination for design and analysis of structures with ever smaller features and multi-resonant and broadband. This geometry has been applied in such patch microstrip antennas to reduce its size and highlight its multi-band behavior. Compared with the conventional microstrip antennas, the quasifractal patch antennas have lower frequencies of resonance, enabling the manufacture of more compact antennas. The aim of this work is the design of quasi-fractal patch antennas through the use of Koch and Minkowski fractal curves applied to radiating and nonradiating antenna s edges of conventional rectangular patch fed by microstrip inset-fed line, initially designed for the frequency of 2.45 GHz. The inset-fed technique is investigated for the impedance matching of fractal antennas, which are fed through lines of microstrip. The efficiency of this technique is investigated experimentally and compared with simulations carried out by commercial software Ansoft Designer used for precise analysis of the electromagnetic behavior of antennas by the method of moments and the neural model proposed. In this dissertation a study of literature on theory of microstrip antennas is done, the same study is performed on the fractal geometry, giving more emphasis to its various forms, techniques for generation of fractals and its applicability. This work also presents a study on artificial neural networks, showing the types/architecture of networks used and their characteristics as well as the training algorithms that were used for their implementation. The equations of settings of the parameters for networks used in this study were derived from the gradient method. It will also be carried out research with emphasis on miniaturization of the proposed new structures, showing how an antenna designed with contours fractals is capable of a miniaturized antenna conventional rectangular patch. The study also consists of a modeling through artificial neural networks of the various parameters of the electromagnetic near-fractal antennas. The presented results demonstrate the excellent capacity of modeling techniques for neural microstrip antennas and all algorithms used in this work in achieving the proposed models were implemented in commercial software simulation of Matlab 7. In order to validate the results, several prototypes of antennas were built, measured on a vector network analyzer and simulated in software for comparison

Modelagem e controle de um microveículo aéreo: uma aplicação de estabilidade robusta com a técnica backstepping em uma estrutura hexarrotor

In this Thesis, the development of the dynamic model of multirotor unmanned aerial vehicle with vertical takeoff and landing characteristics, considering input nonlinearities and a full state robust backstepping controller are presented. The dynamic model is expressed using the Newton-Euler laws, aiming to obtain a better mathematical representation of the mechanical system for system analysis and control design, not only when it is hovering, but also when it is taking-off, or landing, or flying to perform a task. The input nonlinearities are the deadzone and saturation, where the gravitational effect and the inherent physical constrains of the rotors are related and addressed. The experimental multirotor aerial vehicle is equipped with an inertial measurement unit and a sonar sensor, which appropriately provides measurements of attitude and altitude. A real-time attitude estimation scheme based on the extended Kalman filter using quaternions was developed. Then, for robustness analysis, sensors were modeled as the ideal value with addition of an unknown bias and unknown white noise. The bounded robust attitude/altitude controller were derived based on globally uniformly practically asymptotically stable for real systems, that remains globally uniformly asymptotically stable if and only if their solutions are globally uniformly bounded, dealing with convergence and stability into a ball of the state space with non-null radius, under some assumptions. The Lyapunov analysis technique was used to prove the stability of the closed-loop system, compute bounds on control gains and guaranteeing desired bounds on attitude dynamics tracking errors in the presence of measurement disturbances. The controller laws were tested in numerical simulations and in an experimental hexarotor, developed at the UFRN Robotics Laboratory

Modelagem de máquina de indução trifásica sem mancais com bobinado dividido

This work presents a model of bearingless induction machine with divided winding. The main goal is to obtain a machine model to use a simpler control system as used in conventional induction machine and to know its behavior. The same strategies used in conventional machines were used to reach the bearingless induction machine model, which has made possible an easier treatment of the involved parameters. The studied machine is adapted from the conventional induction machine, the stator windings were divided and all terminals had been available. This method does not need an auxiliary stator winding for the radial position control which results in a more compact machine. Another issue about this machine is the variation of inductances array also present in result of the rotor displacement. The changeable air-gap produces variation in magnetic flux and in inductances consequently. The conventional machine model can be used for the bearingless machine when the rotor is centered, but in rotor displacement condition this model is not applicable. The bearingless machine has two sets of motor-bearing, both sets with four poles. It was constructed in horizontal position and this increases difficulty in implementation. The used rotor has peculiar characteristics; it is projected according to the stator to yield the greatest torque and force possible. It is important to observe that the current unbalance generated by the position control does not modify the machine characteristics, this only occurs due the radial rotor displacement. The obtained results validate the work; the data reached by a supervisory system corresponds the foreseen results of simulation which verify the model veracity

Modelagem e medições de ondas de rádio para predição de perda de propagação em ambientes urbanos

In this dissertation new models of propagation path loss predictions are proposed by from techniques of optimization recent and measures of power levels for the urban and suburban areas of Natal, city of Brazilian northeast. These new proposed models are: (i) a statistical model that was implemented based in the addition of second-order statistics for the power and the altimetry of the relief in model of linear losses; (ii) a artificial neural networks model used the training of the algorithm backpropagation, in order to get the equation of propagation losses; (iii) a model based on the technique of the random walker, that considers the random of the absorption and the chaos of the environment and than its unknown parameters for the equation of propagation losses are determined through of a neural network. The digitalization of the relief for the urban and suburban areas of Natal were carried through of the development of specific computational programs and had been used available maps in the Statistics and Geography Brazilian Institute. The validations of the proposed propagation models had been carried through comparisons with measures and propagation classic models, and numerical good agreements were observed. These new considered models could be applied to any urban and suburban scenes with characteristic similar architectural to the city of Natal

Aplicação de sistemas multi-classificadores no diagnóstico de falhas em motores de indução trifásicos

Equipment maintenance is the major cost factor in industrial plants, it is very important the development of fault predict techniques. Three-phase induction motors are key electrical equipments used in industrial applications mainly because presents low cost and large robustness, however, it isn t protected from other fault types such as shorted winding and broken bars. Several acquisition ways, processing and signal analysis are applied to improve its diagnosis. More efficient techniques use current sensors and its signature analysis. In this dissertation, starting of these sensors, it is to make signal analysis through Park s vector that provides a good visualization capability. Faults data acquisition is an arduous task; in this way, it is developed a methodology for data base construction. Park s transformer is applied into stationary reference for machine modeling of the machine s differential equations solution. Faults detection needs a detailed analysis of variables and its influences that becomes the diagnosis more complex. The tasks of pattern recognition allow that systems are automatically generated, based in patterns and data concepts, in the majority cases undetectable for specialists, helping decision tasks. Classifiers algorithms with diverse learning paradigms: k-Neighborhood, Neural Networks, Decision Trees and Naïves Bayes are used to patterns recognition of machines faults. Multi-classifier systems are used to improve classification errors. It inspected the algorithms homogeneous: Bagging and Boosting and heterogeneous: Vote, Stacking and Stacking C. Results present the effectiveness of constructed model to faults modeling, such as the possibility of using multi-classifiers algorithm on faults classification

Modelagem em SystemC-AMS de uma plataforma compatível com o sistema de coleta de dados brasileiro

This work presents simulation results of an identification platform compatible with the INPE Brazilian Data Collection System, modeled with SystemC-AMS. SystemC-AMS that is a library of C++ classes dedicated to the simulation of heterogeneous systems, offering a powerful resource to describe models in digital, analog and RF domains, as well as mechanical and optic. The designed model was divided in four parts. The first block takes into account the satellite s orbit, necessary to correctly model the propagation channel, including Doppler effect, attenuation and thermal noise. The identification block detects the satellite presence. It is composed by low noise amplifier, band pass filter, power detector and logic comparator. The controller block is responsible for enabling the RF transmitter when the presence of the satellite is detected. The controller was modeled as a Petri net, due to the asynchronous nature of the system. The fourth block is the RF transmitter unit, which performs the modulation of the information in BPSK ±60o. This block is composed by oscillator, mixer, adder and amplifier. The whole system was simulated simultaneously. The results are being used to specify system components and to elaborate testbenchs for design verification

Modelagem aplicada à análise de desempenho do provedor de serviços de uma rede de automação hospitalar ieee 802.3/pm-ah de tempo real

The incorporate of industrial automation in the medical are requires mechanisms to safety and efficient establishment of communication between biomedical devices. One solution to this problem is the MP-HA (Multicycles Protocol to Hospital Automation) that down a segmented network by beds coordinated by an element called Service Provider. The goal of this work is to model this Service Provider and to do performance analysis of the activities executed by in establishment and maintenance of hospital networks

Modelagem de usinas eólicas através de um processo de Markov e técnicas de confiabilidade para a estimativa anual da energia produzida

This study aims to use a computational model that considers the statistical characteristics of the wind and the reliability characteristics of a wind turbine, such as failure rates and repair, representing the wind farm by a Markov process to determine the estimated annual energy generated, and compare it with a real case. This model can also be used in reliability studies, and provides some performance indicators that will help in analyzing the feasibility of setting up a wind farm, once the power curve is known and the availability of wind speed measurements. To validate this model, simulations were done using the database of the wind farm of Macau PETROBRAS. The results were very close to the real, thereby confirming that the model successfully reproduced the behavior of all components involved. Finally, a comparison was made of the results presented by this model, with the result of estimated annual energy considering the modeling of the distribution wind by a statistical distribution of Weibull

Caracterização de antenas planares com substrato metamaterial

This work presents a theoretical and numerical analysis for the radiation characteristics of rectangular microstrip antenna using metamaterial substrate. The full wave analysis is performed in the Fourier transform domain through the application of the Transverse Transmission Line - TTL method. A study on metamaterial theory was conducted to obtain the constructive parameters, which were characterized through permittivity and permeability tensors to arrive at a set of electromagnetic equations. The general equations for the electromagnetic fields of the antenna are developed using the Transverse Transmission Line - TTL method. Imposing the boundary conditions, the dyadic Green s function components are obtained relating the surface current density components at the plane of the patch to the electric field tangential components. Then, Galerkin s method is used to obtain a system of matrix equations, whose solution gives the antenna resonant frequency. From this modeling, it is possible to obtain numerical results for the resonant frequency and return loss for different configurations and substrates

Aplicação de técnicas de aprendizado de máquina no reconhecimento de classes estruturais de proteínas

Nowadays, classifying proteins in structural classes, which concerns the inference of patterns in their 3D conformation, is one of the most important open problems in Molecular Biology. The main reason for this is that the function of a protein is intrinsically related to its spatial conformation. However, such conformations are very difficult to be obtained experimentally in laboratory. Thus, this problem has drawn the attention of many researchers in Bioinformatics. Considering the great difference between the number of protein sequences already known and the number of three-dimensional structures determined experimentally, the demand of automated techniques for structural classification of proteins is very high. In this context, computational tools, especially Machine Learning (ML) techniques, have become essential to deal with this problem. In this work, ML techniques are used in the recognition of protein structural classes: Decision Trees, k-Nearest Neighbor, Naive Bayes, Support Vector Machine and Neural Networks. These methods have been chosen because they represent different paradigms of learning and have been widely used in the Bioinfornmatics literature. Aiming to obtain an improvment in the performance of these techniques (individual classifiers), homogeneous (Bagging and Boosting) and heterogeneous (Voting, Stacking and StackingC) multiclassification systems are used. Moreover, since the protein database used in this work presents the problem of imbalanced classes, artificial techniques for class balance (Undersampling Random, Tomek Links, CNN, NCL and OSS) are used to minimize such a problem. In order to evaluate the ML methods, a cross-validation procedure is applied, where the accuracy of the classifiers is measured using the mean of classification error rate, on independent test sets. These means are compared, two by two, by the hypothesis test aiming to evaluate if there is, statistically, a significant difference between them. With respect to the results obtained with the individual classifiers, Support Vector Machine presented the best accuracy. In terms of the multi-classification systems (homogeneous and heterogeneous), they showed, in general, a superior or similar performance when compared to the one achieved by the individual classifiers used - especially Boosting with Decision Tree and the StackingC with Linear Regression as meta classifier. The Voting method, despite of its simplicity, has shown to be adequate for solving the problem presented in this work. The techniques for class balance, on the other hand, have not produced a significant improvement in the global classification error. Nevertheless, the use of such techniques did improve the classification error for the minority class. In this context, the NCL technique has shown to be more appropriated

Modelagem linear e identificação do modelo dinâmico de um robô móvel com acionamento diferencial

This work presents a modelling and identification method for a wheeled mobile robot, including the actuator dynamics. Instead of the classic modelling approach, where the robot position coordinates (x,y) are utilized as state variables (resulting in a non linear model), the proposed discrete model is based on the travelled distance increment Delta_l. Thus, the resulting model is linear and time invariant and it can be identified through classical methods such as Recursive Least Mean Squares. This approach has a problem: Delta_l can not be directly measured. In this paper, this problem is solved using an estimate of Delta_l based on a second order polynomial approximation. Experimental data were colected and the proposed method was used to identify the model of a real robot

Modelagem e controle adaptativo de uma planta didática de nível com instrumentação industrial

The control, automation and optimization areas help to improve the processes used by industry. They contribute to a fast production line, improving the products quality and reducing the manufacturing costs. Didatic plants are good tools for research in these areas, providing a direct contact with some industrial equipaments. Given these capabilities, the main goal of this work is to model and control a didactic plant, which is a level and flow process control system with an industrial instrumentation. With a model it is possible to build a simulator for the plant that allows studies about its behaviour, without any of the real processes operational costs, like experiments with controllers. They can be tested several times before its application in a real process. Among the several types of controllers, it was used adaptive controllers, mainly the Direct Self-Tuning Regulators (DSTR) with Integral Action and the Gain Scheduling (GS). The DSTR was based on Pole-Placement design and use the Recursive Least Square to calculate the controller parameters. The characteristics of an adaptive system was very worth to guarantee a good performance when the controller was applied to the plant

Desgaste de polímeros estruturais de engenharia em contato de deslizamento com cilindro metálico

Present work proposed to map and features the wear mechanisms of structural polymers of engineering derived of the sliding contact with a metallic cylindrical spindle submitted to eccentricity due to fluctuations in it is mass and geometric centers. For this it was projected and makes an experimental apparatus from balancing machine where the cylindrical counterbody was supported in two bearings and the polymeric coupon was situated in a holder with freedom of displacement along counterbody. Thus, the experimental tests were standardized using two position of the two bearings (Fixed or Free) and seven different positions along the counterbody, that permit print different conditions to the stiffness from system. Others parameters as applied normal load, sliding velocity and distance were fixed. In this investigation it was used as coupon two structural polymers of wide quotidian use, PTFE (polytetrafluroethylene) and PEEK (poly-ether-ether-ketone) and the AISI 4140 alloy steel as counterbody. Polymeric materials were characterized by thermal analysis (thermogravimetric, differential scanning calorimetry and dynamic-mechanical), hardness and rays-X diffractometry. While the metallic material was submitted at hardness, mechanical resistance tests and metallographic analysis. During the tribological tests were recorded the heating response with thermometers, yonder overall velocity vibration (VGV) and the acceleration using accelerometers. After tests the wear surface of the coupons were analyzed using a Scanning Electronic Microscopy (SEM) to morphological analysis and spectroscopy EDS to microanalysis. Moreover the roughness of the counterbody was characterized before and after the tribological tests. It was observed that the tribological response of the polymers were different in function of their distinct molecular structure. It were identified the predominant wear mechanisms in each polymer. The VGV of the PTFE was smaller than PEEK, in the condition of minimum stiffness, in function of the higher loss coefficient of that polymer. Wear rate of the PTFE was more of a magnitude order higher than PEEK. With the results was possible developed a correlation between the wear rate and parameter (E/ρ)1/2 (Young modulus, E, density, ρ), proportional at longitudinal elastic wave velocity in the material.

Efeito da adição de argila expandida e adições minerais na formulação de concretos estruturais leves autoadensáveis

The search for alternative materials with lower density, reduction in heat transfer and propagation of noise associated with the ease of handling and application in concrete structures, represents an enormous challenge in the formulation and knowledge of the performance of self-compacting lightweight concrete, which has technology little known nationally, and appears on the international scene as an innovative material and alternative to conventional concrete. Based on these, this study set out to study self-compacting lightweight concrete made with two distinct grades of expanded clay associated with the addition of plasticizing/superplasticizers additives and mineral additions of metakaolin and bagasse ash of sugar cane. There is also an object of study, evaluation of pozzolanic activity of mineral admixtures and their influence on the durability characteristics of concrete. The rheological, physical, mechanical and microstructural analysis in this study served as basis in the classification of concretes autoadensáveis, targeting the national technical requirements for their classification in the category autoadensável and lightweight structural. The inclusion of mineral admixtures (metakaolin and bagasse ash of sugar cane), partial replacement of cement, pozzolanic activity and demonstrated maintenance of mechanical properties through the filler effect, a reduction of up to 76% of the nitrogen gas permeability in blend with 20% bagasse ash. All concretes had rheology (cohesion and consistency) suitable for self-adensability as well as strength and density inherent structural lightweight concrete without presenting phenomena of segregation and exudation