59 resultados para synsedimentary faults

em Universidade Federal do Rio Grande do Norte(UFRN)


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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

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In the last decades, the oil, gas and petrochemical industries have registered a series of huge accidents. Influenced by this context, companies have felt the necessity of engaging themselves in processes to protect the external environment, which can be understood as an ecological concern. In the particular case of the nuclear industry, sustainable education and training, which depend too much on the quality and applicability of the knowledge base, have been considered key points on the safely application of this energy source. As a consequence, this research was motivated by the use of the ontology concept as a tool to improve the knowledge management in a refinery, through the representation of a fuel gas sweetening plant, mixing many pieces of information associated with its normal operation mode. In terms of methodology, this research can be classified as an applied and descriptive research, where many pieces of information were analysed, classified and interpreted to create the ontology of a real plant. The DEA plant modeling was performed according to its process flow diagram, piping and instrumentation diagrams, descriptive documents of its normal operation mode, and the list of all the alarms associated to the instruments, which were complemented by a non-structured interview with a specialist in that plant operation. The ontology was verified by comparing its descriptive diagrams with the original plant documents and discussing with other members of the researchers group. All the concepts applied in this research can be expanded to represent other plants in the same refinery or even in other kind of industry. An ontology can be considered a knowledge base that, because of its formal representation nature, can be applied as one of the elements to develop tools to navigate through the plant, simulate its behavior, diagnose faults, among other possibilities

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The theme of the research is inserted at a field of intersection between the Sociology of Religion and Sociology of Violence, having as the general objective study the sociological meaning of the conversion of prisoners that lives at the biggest prison (Prison of Alcaçuz) of Rio Grande do Norte to the evangelical churches. The research is justified, because Brazil shelter the fourth greater arrested population arrested of the world, with projections indicating that it can turn the greatest in 2034. Besides, this study about religious conversion of prisoners to the Social Sciences is too important, because is a theme little developed in Brazil and deserves attention, one time that as the arrested people as the evangelicals are in expansion in our country. Starting from the precedent observations, we guide ourselves by the following problematic of research: the religious practice in Alcaçuz presents a mere instrumental perspective, where the actions of prisoners converted was on purpose oriented to conquest material or symbolic privileges; or purely religious, where seek a moral renovation? To develop the work, the scientific methodology adopted was exploratory and explanatory, using the Goffman´s theory about total institutions and presentation of self, and Blumer´s doctrine relating to Symbolic Interacionism and the Story life method, besides considerations about evangelical religion. Having this theoretical basis, was accomplished the Field research, when were made interviews and applied questionnaires to 11 Jailer Agents, 31 prisoners, Director and Vice-Dictor (in November, 2011), the coordinator of social projects of the prison and the coordinator of evangelization at the prisons in Rio Grande do Norte. As results, it was seeing in Alcaçuz that the prisoners can be separated in two groups: the one of Pavilions and other one of the Medical Section. The Pavilions are branded for managerial and structural problems, where are found idle prisoners in collective cells and with a historical of escaping attempts, mutinies and murders. The Medical Section has some individual cells or destined for two people, besides few collective also, and the prisoners work and have a more disciplined behavior, there isn t escapes or rebellions and that, for these reasons end for have more confidence from the Administration. About the presence of evangelical prisoners, most are at Medical Section, where exist a specific place to the cults (what doesn t at Pavilions). At the end, the conclusion is that the prisoner that says himself evangelical in Alcaçuz, although can be seeing with distrust about your real conversion, he gets win a trust vote and until the opposite being demonstrated in other words, that he is not hiding himself behind the bible to divert the vigilance of Direction and practice disciplinary faults without make any suspicions, is treated with more respect and has more opportunities live at Medical Section; have work, that most of times is paid and guarantee the homologation of your payment of penalty with work, besides other benefits, diminishing his time in jail

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The work presented here is about aspects of the constitutional extension in which is the public civil action with the objective of verifying its aptitute in tutelaging subjective situations derived from fundamental rights, especially right to health assistance. Thus, it offers a clear analysis of the practical functioning of most aspects of the public civil action (lawsuit), with philosophical foundation and necessary doctrinaire to your comphehension. How it once was (history), how it could be (reform suggestion), how it is (current interpretation of the law) and how it should be (critic analysis of the microsystem of collective tutelaging of rights, its perspectives, as well as the efficacy of the public cilvil action about accomplishment of the right to health as supraindividual right). The objective is to analyse the main version of the theme (for instance: the impacts caused to the dissociation of the Procurations theory), so that it can be extracted the philosophy and the general theory, of the public civil action and collective tutelaging in general, pragmatically applicable to study purposes. With this theorical fountain, the reader will be in a more solid position, not only being able to understand the subtilities of the public civil action, but mainly being able to recognize its faults and present solid reform proposals and improvement. It is know that the Juridical Power (Procuration) does not allow any more inactivity about negating accession to health in its collective dimension (lato sensu: spread, collective stricto sensu and homogeneous individuals), being imputed to it novel usage that consolidates in the assumption of the role instrument set aside to be used by all with organized instancy of solution to collective conflicts in large sense. This happens, overall, because of the current justice politization, understood as juridical activism, connected to the struggle between the groups defending their interests and the acceptance of the constitution about solidifying the public politics of quality health

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The question of participation has been debated in Brazil since the 1980 decade in search a better way to take care of poulation s demand. More specificaly after the democratic open (1985) begins to be thought ways to make population participates of decisions related to alocation of public resources. The characteristic of participates actualy doesn t exist, population to be carried through is, at top, consulted, and the fact population participates stays restrict to some technics interests at the projects, mainly of public politics of local development. Observe that this implementation happens through a process and that has its limits (pass) that could be surpassed through strategies made to that. This dissertation shows results of a research about participative practices in city of Serrinha between 1997 and 2004, showing through a study of the case of Serrinha what was the process used to carry through these pratices in a moment and local considered model of this application. The analyses were developed through a model of research elaborated by the author based on large literature respects the ideal process to implant a participative public politics. The present research had a qualitative boarding, being explorative and descritive nature. The researcher (author of this dissertation) carried through all the research phases, including the transcriptions of interviews that were recorded with a digital voice recorder. Before the analysis of these data was verified that despite the public manager (former-mayor) had had a real interest in implant a process of local development in city, he was not able to forsee the correct process to do it. Two high faults were made. The first was the intention to have as tool a development plan, what locked up to make this plan was the booster of supossed participative pratice and no the ideal model that would be a plan generate by popular initiative. The second one was absence of a critical education project for the population that should be the fisrt step to carry through a politc like that

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This master dissertation presents the development of a fault detection and isolation system based in neural network. The system is composed of two parts: an identification subsystem and a classification subsystem. Both of the subsystems use neural network techniques with multilayer perceptron training algorithm. Two approaches for identifica-tion stage were analyzed. The fault classifier uses only residue signals from the identification subsystem. To validate the proposal we have done simulation and real experiments in a level system with two water reservoirs. Several faults were generated above this plant and the proposed fault detection system presented very acceptable behavior. In the end of this work we highlight the main difficulties found in real tests that do not exist when it works only with simulation environments

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At present, the electricity generation through wind energy has an importance growing in the world, with the existence of very large plans for future wind power installation worldwide. Thus, the increasing the electricity generation through wind power requires, more and more, analysis of studies of interaction between wind parks and electric power systems. This paper has as purposes to implement equivalent models for synchronous wind generators to represent a wind park in ATP program and to check behavior of the models through simulations. Simulations with applications of faults were achieved to evaluate the behavior of voltages of system for each equivalent model, through comparisons between the results of models proposed, to verify if the differences obtained allows the adoption of the simplest model

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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

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The industries are getting more and more rigorous, when security is in question, no matter is to avoid financial damages due to accidents and low productivity, or when it s related to the environment protection. It was thinking about great world accidents around the world involving aircrafts and industrial process (nuclear, petrochemical and so on) that we decided to invest in systems that could detect fault and diagnosis (FDD) them. The FDD systems can avoid eventual fault helping man on the maintenance and exchange of defective equipments. Nowadays, the issues that involve detection, isolation, diagnose and the controlling of tolerance fault are gathering strength in the academic and industrial environment. It is based on this fact, in this work, we discuss the importance of techniques that can assist in the development of systems for Fault Detection and Diagnosis (FDD) and propose a hybrid method for FDD in dynamic systems. We present a brief history to contextualize the techniques used in working environments. The detection of fault in the proposed system is based on state observers in conjunction with other statistical techniques. The principal idea is to use the observer himself, in addition to serving as an analytical redundancy, in allowing the creation of a residue. This residue is used in FDD. A signature database assists in the identification of system faults, which based on the signatures derived from trend analysis of the residue signal and its difference, performs the classification of the faults based purely on a decision tree. This FDD system is tested and validated in two plants: a simulated plant with coupled tanks and didactic plant with industrial instrumentation. All collected results of those tests will be discussed

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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

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This work presents a packet manipulation tool developed to realize tests in industrial devices that implements TCP/IP-based communication protocols. The tool was developed in Python programming language, as a Scapy extension. This tool, named IndPM- Industrial Packet Manipulator, can realize vulnerability tests in devices of industrial networks, industrial protocol compliance tests, receive server replies and utilize the Python interpreter to build tests. The Modbus/TCP protocol was implemented as proof-of-concept. The DNP3 over TCP protocol was also implemented but tests could not be realized because of the lack of resources. The IndPM results with Modbus/TCP protocol show some implementation faults in a Programmable Logic Controller communication module frequently utilized in automation companies

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This work presents a diagnosis faults system (rotor, stator, and contamination) of three-phase induction motor through equivalent circuit parameters and using techniques patterns recognition. The technology fault diagnostics in engines are evolving and becoming increasingly important in the field of electrical machinery. The neural networks have the ability to classify non-linear relationships between signals through the patterns identification of signals related. It is carried out induction motor´s simulations through the program Matlab R & Simulink R , and produced some faults from modifications in the equivalent circuit parameters. A system is implemented with multiples classifying neural network two neural networks to receive these results and, after well-trained, to accomplish the identification of fault´s pattern

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In a real process, all used resources, whether physical or developed in software, are subject to interruptions or operational commitments. However, in situations in which operate critical systems, any kind of problem may bring big consequences. Knowing this, this paper aims to develop a system capable to detect the presence and indicate the types of failures that may occur in a process. For implementing and testing the proposed methodology, a coupled tank system was used as a study model case. The system should be developed to generate a set of signals that notify the process operator and that may be post-processed, enabling changes in control strategy or control parameters. Due to the damage risks involved with sensors, actuators and amplifiers of the real plant, the data set of the faults will be computationally generated and the results collected from numerical simulations of the process model. The system will be composed by structures with Artificial Neural Networks, trained in offline mode using Matlab®

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Induction motors are one of the most important equipment of modern industry. However, in many situations, are subject to inadequate conditions as high temperatures and pressures, load variations and constant vibrations, for example. Such conditions, leaving them more susceptible to failures, either external or internal in nature, unwanted in the industrial process. In this context, predictive maintenance plays an important role, where the detection and diagnosis of faults in a timely manner enables the increase of time of the engine and the possibiity of reducing costs, caused mainly by stopping the production and corrective maintenance the motor itself. In this juncture, this work proposes the design of a system that is able to detect and diagnose faults in induction motors, from the collection of electrical line voltage and current, and also the measurement of engine speed. This information will use as input to a fuzzy inference system based on rules that find and classify a failure from the variation of thess quantities

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This work consists of the creation of a Specialist System which utilizes production rules to detect inadequacies in the command circuits of an operation system and commands of electric engines known as Direct Start. Jointly, three other modules are developed: one for the simulation of the commands diagram, one for the simulation of faults and another one for the correction of defects in the diagram, with the objective of making it possible to train the professionals aiming a better qualification for the operation and maintenance. The development is carried through in such a way that the structure of the task allows the extending of the system and a succeeding promotion of other bigger and more complex typical systems. The computational environment LabView is employed to enable the system