14 resultados para Control de processos -- Mètodes estadístics

em Universidade Federal do Rio Grande do Norte(UFRN)


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The petrochemical industry has as objective obtain, from crude oil, some products with a higher commercial value and a bigger industrial utility for energy purposes. These industrial processes are complex, commonly operating with large production volume and in restricted operation conditions. The operation control in optimized and stable conditions is important to keep obtained products quality and the industrial plant safety. Currently, industrial network has been attained evidence when there is a need to make the process control in a distributed way. The Foundation Fieldbus protocol for industrial network, for its interoperability feature and its user interface organized in simple configuration blocks, has great notoriety among industrial automation network group. This present work puts together some benefits brought by industrial network technology to petrochemical industrial processes inherent complexity. For this, a dynamic reconfiguration system for intelligent strategies (artificial neural networks, for example) based on the protocol user application layer is proposed which might allow different applications use in a particular process, without operators intervention and with necessary guarantees for the proper plant functioning

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The oscillations presents in control loops can cause damages in petrochemical industry. Canceling, or even preventing such oscillations, would save up to large amount of dollars. Studies have identified that one of the causes of these oscillations are the nonlinearities present on industrial process actuators. This study has the objective to develop a methodology for removal of the harmful effects of nonlinearities. Will be proposed an parameter estimation method to Hammerstein model, whose nonlinearity is represented by dead-zone or backlash. The estimated parameters will be used to construct inverse models of compensation. A simulated level system was used as a test platform. The valve that controls inflow has a nonlinearity. Results and describing function analysis show an improvement on system response

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A pesquisa tem como objetivo desenvolver uma estrutura de controle preditivo neural, com o intuito de controlar um processo de pH, caracterizado por ser um sistema SISO (Single Input - Single Output). O controle de pH é um processo de grande importância na indústria petroquímica, onde se deseja manter constante o nível de acidez de um produto ou neutralizar o afluente de uma planta de tratamento de fluidos. O processo de controle de pH exige robustez do sistema de controle, pois este processo pode ter ganho estático e dinâmica nãolineares. O controlador preditivo neural envolve duas outras teorias para o seu desenvolvimento, a primeira referente ao controle preditivo e a outra a redes neurais artificiais (RNA s). Este controlador pode ser dividido em dois blocos, um responsável pela identificação e outro pelo o cálculo do sinal de controle. Para realizar a identificação neural é utilizada uma RNA com arquitetura feedforward multicamadas com aprendizagem baseada na metodologia da Propagação Retroativa do Erro (Error Back Propagation). A partir de dados de entrada e saída da planta é iniciado o treinamento offline da rede. Dessa forma, os pesos sinápticos são ajustados e a rede está apta para representar o sistema com a máxima precisão possível. O modelo neural gerado é usado para predizer as saídas futuras do sistema, com isso o otimizador calcula uma série de ações de controle, através da minimização de uma função objetivo quadrática, fazendo com que a saída do processo siga um sinal de referência desejado. Foram desenvolvidos dois aplicativos, ambos na plataforma Builder C++, o primeiro realiza a identificação, via redes neurais e o segundo é responsável pelo controle do processo. As ferramentas aqui implementadas e aplicadas são genéricas, ambas permitem a aplicação da estrutura de controle a qualquer novo processo

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The using of supervision systems has become more and more essential in accessing, managing and obtaining data of industrial processes, because of constant and frequent developments in industrial automation. These supervisory systems (SCADA) have been widely used in many industrial environments to store process data and to control the processes in accordance with some adopted strategy. The SCADA s control hardware is the set of equipments that execute this work. The SCADA s supervision software accesses process data through the control hardware and shows them to the users. Currently, many industrial systems adopt supervision softwares developed by the same manufacturer of the control hardware. Usually, these softwares cannot be used with other equipments made by distinct manufacturers. This work proposes an approach for developing supervisory systems able to access process information through different control hardwares. An architecture for supervisory systems is first defined, in order to guarantee efficiency in communication and data exchange. Then, the architecture is applied in a supervisory system to monitor oil wells that use distinct control hardwares. The implementation was modeled and verified by using the formal method of the Petri networks. Finally, experimental results are presented to demonstrate the applicability of the proposed solution

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Slugging is a well-known slugging phenomenon in multiphase flow, which may cause problems such as vibration in pipeline and high liquid level in the separator. It can be classified according to the place of its occurrence. The most severe, known as slugging in the riser, occurs in the vertical pipe which feeds the platform. Also known as severe slugging, it is capable of causing severe pressure fluctuations in the flow of the process, excessive vibration, flooding in separator tanks, limited production, nonscheduled stop of production, among other negative aspects that motivated the production of this work . A feasible solution to deal with this problem would be to design an effective method for the removal or reduction of the system, a controller. According to the literature, a conventional PID controller did not produce good results due to the high degree of nonlinearity of the process, fueling the development of advanced control techniques. Among these, the model predictive controller (MPC), where the control action results from the solution of an optimization problem, it is robust, can incorporate physical and /or security constraints. The objective of this work is to apply a non-conventional non-linear model predictive control technique to severe slugging, where the amount of liquid mass in the riser is controlled by the production valve and, indirectly, the oscillation of flow and pressure is suppressed, while looking for environmental and economic benefits. The proposed strategy is based on the use of the model linear approximations and repeatedly solving of a quadratic optimization problem, providing solutions that improve at each iteration. In the event where the convergence of this algorithm is satisfied, the predicted values of the process variables are the same as to those obtained by the original nonlinear model, ensuring that the constraints are satisfied for them along the prediction horizon. A mathematical model recently published in the literature, capable of representing characteristics of severe slugging in a real oil well, is used both for simulation and for the project of the proposed controller, whose performance is compared to a linear MPC

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A chemical process optimization and control is strongly correlated with the quantity of information can be obtained from the system. In biotechnological processes, where the transforming agent is a cell, many variables can interfere in the process, leading to changes in the microorganism metabolism and affecting the quantity and quality of final product. Therefore, the continuously monitoring of the variables that interfere in the bioprocess, is crucial to be able to act on certain variables of the system, keeping it under desirable operational conditions and control. In general, during a fermentation process, the analysis of important parameters such as substrate, product and cells concentration, is done off-line, requiring sampling, pretreatment and analytical procedures. Therefore, this steps require a significant run time and the use of high purity chemical reagents to be done. In order to implement a real time monitoring system for a benchtop bioreactor, these study was conducted in two steps: (i) The development of a software that presents a communication interface between bioreactor and computer based on data acquisition and process variables data recording, that are pH, temperature, dissolved oxygen, level, foam level, agitation frequency and the input setpoints of the operational parameters of the bioreactor control unit; (ii) The development of an analytical method using near-infrared spectroscopy (NIRS) in order to enable substrate, products and cells concentration monitoring during a fermentation process for ethanol production using the yeast Saccharomyces cerevisiae. Three fermentation runs were conducted (F1, F2 and F3) that were monitored by NIRS and subsequent sampling for analytical characterization. The data obtained were used for calibration and validation, where pre-treatments combined or not with smoothing filters were applied to spectrum data. The most satisfactory results were obtained when the calibration models were constructed from real samples of culture medium removed from the fermentation assays F1, F2 and F3, showing that the analytical method based on NIRS can be used as a fast and effective method to quantify cells, substrate and products concentration what enables the implementation of insitu real time monitoring of fermentation processes

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Through out the course of a steady increase in search and recovery of space in the coastal zone, there is also an expanding concern about the erosion processes of this area. The main problem in coastal areas is that urbanization occurs in a disorderly fashion and unsustainable, further aggravating the problems of coastal dynamics. The study area of this work is located on the southern coast of Pirangi do Norte beach to about 20km south of Natal, capital of Rio Grande do Norte in the Parnamirim City. This area has the length of approximately 1km, divided into three sections (Western, Central and Eastern) with a morphology consisting of a tableland at the top, sea cliffs in the West and Central parts and sand dunes in the Eastern section, both vegetated, and a coastal plain on the inferior part associated with the presence of beach rocks. This study aimed to analyze the erosion processes operating in the excerpt of Pirangi do Norte beach and assess the feasibility of their monitoring making use of DGPS (Global Positioning System Differential mode). During the work it was carried out a physical description of the area through photo-interpretation and site survey after measurement of the shoreline in the period between November 2004 and November 2009 and beach profiles between August 2005 and July 2006. The analysis of the results of the annual surveys showed the occurrence of variations of the shoreline along the stretch traveled. Sites are identified in advancement coast from the sea and it was verified in loco the presence of erosion with deposition of materials on the lower part of the coastal bluff, the former position of the shoreline, showing a false notion of advancing it. This leads to the conclusion that the data collected in a survey of the shoreline should always be accompanied by photographic records of the local area and with the highest rate of erosion, thus avoiding the mistake of treating the deposit materials as evidence of progress coast. At the end of the study, after a review of various works to mitigate the erosion in the coastal zone, it is recommended to the area of study the adoption of an artificial feeding of the beach, aiming the minimization of the erosive effects of the tides. Moreover, it is suggested that even the continuity of monitoring, maintenance of existing vegetation and control of the occupation on the edge of sea cliffs

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Systemic lupus erythematous (SLE) is a chronic and auto-immune disease that can affect several systems of one´s body, including the nervous system, causing several clinical evidences, which can put in risk the person´s life. Although the illness could manifest itself at any age or sex, studies indicate higher incidence among women. Its etiology points to the combination of genetic, hormonal and environmental factors. Due to the disease´s complexity, it is evident that it affects all the person´s life as a whole and not only its organic dimension. It is believed that the signification attributed to all the process of sickening influences its treatment, as well as the person´s capacity to cope with the difficulties and implicit profits involved in the process.In this study, eight women who were affected by SLE were interviewed, with the aim of examining carefully the processes of signification as well as the generation of meanings which permeate these women´s sickening processes. The analysis of their speeches evidences distinct forms of giving meaning to the process, regardless of the time of the diagnosis. The fact that the disease is incurable was shocking to all the participants, and it demanded changes in their lives, in order to detain a relative control of their condition. The majority of the participants were able to deal with these modifications, since strategies have been created to face the difficulties and thus to preserve their social life, without damaging their health. However, some of the participants did not obtain strenght to cope with the disease, eventually developing a depressive state. It is observed that not only SLE has innumerable ways of manifestation, but the experience of the illness is very subjective and dynamic. There are also several ways of expressing this experience, according to the implications in the social, cultural and economic context where the participants are inserted. This ratifies the necessity of a interdisciplinary approach to embrace SLE complexity. (310 words, 1.610 characters)

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Web services are computational solutions designed according to the principles of Service Oriented Computing. Web services can be built upon pre-existing services available on the Internet by using composition languages. We propose a method to generate WS-BPEL processes from abstract specifications provided with high-level control-flow information. The proposed method allows the composition designer to concentrate on high-level specifi- cations, in order to increase productivity and generate specifications that are independent of specific web services. We consider service orchestrations, that is compositions where a central process coordinates all the operations of the application. The process of generating compositions is based on a rule rewriting algorithm, which has been extended to support basic control-flow information.We created a prototype of the extended refinement method and performed experiments over simple case studies

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Para la lingüística Cognitiva, la construcción del sentido darse a través del accionamiento de procesos mentales específicos que están directamente ligados a las experiencias socioculturales, sensorio motores y perceptuales. En portadores de la Síndrome de Asperger, el comprometimiento de estos procesos, debido a características específicas dela propia síndrome, puede estar directamente relacionado a problemas de construcción de sentido por estos individuos. En este sentido, el objetivo de esta investigación es investigar los procesos cognitivos que direccionan la construcción del sentido en estos portadores de trastornos neurales. La investigación es realizada con alumnos de la APPARN (Associação de país e amigos dos autistas do Rio Grande do Norte), teniendo como grupo de control alumnos neurotípicos de otras instituciones, siendo los portadores de la síndrome practicantes de la lengua materna o grupo experimental de la búsqueda. Para elucidar el proceso de construcción del sentido por estos alumno, fueron desarrollados testes contiendo rasgos linguisticos norteadores responsables por el accionamiento de algunos procesos cognitivos como los esquemas (JOHNSON, 1987), frames (MINSKY, 1974), affordances (GIBSON, 1979) y simulación mental (BARSALOU, 1999). Los testes fueron basados en los presupuestos teóricos de la Lingüística Cognitiva, más precisamente, de la Teoria Neural del Linguaje. Los resultados apuntan para una posible justificativa para el comprometimiento de la construcción del sentido en portadores de la Síndrome de Asperger, que comprende directamente la relevancia intersubjetiva de la infersencias recibidas y construidas socialmente por los participantes específicamente de este análisis.

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This work proposes a modified control chart incorporating concepts of time series analysis. Specifically, we considerer Gaussian mixed transition distribution (GMTD) models. The GMTD models are a more general class than the autorregressive (AR) family, in the sense that the autocorrelated processes may present flat stretches, bursts or outliers. In this scenario traditional Shewhart charts are no longer appropriate tools to monitoring such processes. Therefore, Vasilopoulos and Stamboulis (1978) proposed a modified version of those charts, considering proper control limits based on autocorrelated processes. In order to evaluate the efficiency of the proposed technique a comparison with a traditional Shewhart chart (which ignores the autocorrelation structure of the process), a AR(1) Shewhart control chart and a GMTD Shewhart control chart was made. An analytical expression for the process variance, as well as control limits were developed for a particular GMTD model. The ARL was used as a criteria to measure the efficiency of control charts. The comparison was made based on a series generated according to a GMTD model. The results point to the direction that the modified Shewhart GMTD charts have a better performance than the AR(1) Shewhart and the traditional Shewhart.

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The petrochemical industry has as objective obtain, from crude oil, some products with a higher commercial value and a bigger industrial utility for energy purposes. These industrial processes are complex, commonly operating with large production volume and in restricted operation conditions. The operation control in optimized and stable conditions is important to keep obtained products quality and the industrial plant safety. Currently, industrial network has been attained evidence when there is a need to make the process control in a distributed way. The Foundation Fieldbus protocol for industrial network, for its interoperability feature and its user interface organized in simple configuration blocks, has great notoriety among industrial automation network group. This present work puts together some benefits brought by industrial network technology to petrochemical industrial processes inherent complexity. For this, a dynamic reconfiguration system for intelligent strategies (artificial neural networks, for example) based on the protocol user application layer is proposed which might allow different applications use in a particular process, without operators intervention and with necessary guarantees for the proper plant functioning

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The oscillations presents in control loops can cause damages in petrochemical industry. Canceling, or even preventing such oscillations, would save up to large amount of dollars. Studies have identified that one of the causes of these oscillations are the nonlinearities present on industrial process actuators. This study has the objective to develop a methodology for removal of the harmful effects of nonlinearities. Will be proposed an parameter estimation method to Hammerstein model, whose nonlinearity is represented by dead-zone or backlash. The estimated parameters will be used to construct inverse models of compensation. A simulated level system was used as a test platform. The valve that controls inflow has a nonlinearity. Results and describing function analysis show an improvement on system response

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A pesquisa tem como objetivo desenvolver uma estrutura de controle preditivo neural, com o intuito de controlar um processo de pH, caracterizado por ser um sistema SISO (Single Input - Single Output). O controle de pH é um processo de grande importância na indústria petroquímica, onde se deseja manter constante o nível de acidez de um produto ou neutralizar o afluente de uma planta de tratamento de fluidos. O processo de controle de pH exige robustez do sistema de controle, pois este processo pode ter ganho estático e dinâmica nãolineares. O controlador preditivo neural envolve duas outras teorias para o seu desenvolvimento, a primeira referente ao controle preditivo e a outra a redes neurais artificiais (RNA s). Este controlador pode ser dividido em dois blocos, um responsável pela identificação e outro pelo o cálculo do sinal de controle. Para realizar a identificação neural é utilizada uma RNA com arquitetura feedforward multicamadas com aprendizagem baseada na metodologia da Propagação Retroativa do Erro (Error Back Propagation). A partir de dados de entrada e saída da planta é iniciado o treinamento offline da rede. Dessa forma, os pesos sinápticos são ajustados e a rede está apta para representar o sistema com a máxima precisão possível. O modelo neural gerado é usado para predizer as saídas futuras do sistema, com isso o otimizador calcula uma série de ações de controle, através da minimização de uma função objetivo quadrática, fazendo com que a saída do processo siga um sinal de referência desejado. Foram desenvolvidos dois aplicativos, ambos na plataforma Builder C++, o primeiro realiza a identificação, via redes neurais e o segundo é responsável pelo controle do processo. As ferramentas aqui implementadas e aplicadas são genéricas, ambas permitem a aplicação da estrutura de controle a qualquer novo processo