969 resultados para Automação industrial


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Sabemos todos os que aqui nos encontramos que o “choque do futuro” que é o nosso presente levou muita gente a olhar para o passado.De facto, nesta nossa época de revolução electrónica, das auto-estradas da informação e da desindustrialização, muitos se sentem atraídos com curiosidade e, até, com alguma nostalgia, pelo tempo, pelos vestígios, pelos testemunhos das origens da época industrial que marcou a Europa e o mundo inteiro nos últimos séculos.De resto, o impacto aos níveis pessoal e social que a progressiva automação e as outras aplicações da electrónica vêem causando nos nossos dias e o seu reflexo no plano do imaginário colectivo, não hão-de ser menores, nem muito diferentes do que foram séculos atrás, o impacto causado pelo trabalho das primeiras máquinas ou pela passagem das primeiras composições do caminho de ferro a uma velocidade “estonteante”, quando a sociedade se confrontava ainda com uma tecnologia cujo padrão era a medida do homem.

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The main purpose of this work is to develop an environment that allows HYSYS R chemical process simulator communication with sensors and actuators from a Foundation Fieldbus industrial network. The environment is considered a hybrid resource since it has a real portion (industrial network) and a simulated one (process) with all measurement and control signals also real. It is possible to reproduce different industrial process dynamics without being required any physical network modification, enabling simulation of some situations that exist in a real industrial environment. This feature testifies the environment flexibility. In this work, a distillation column is simulated through HYSYS R with all its variables measured and controlled by Foundation Fieldbus devices

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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

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The rotary dryer is one of the most used equipments in processing industries. Its automatic control mode of operation is important specially to keep the moisture content of the final product in the desired value. The classical control strategies, like PID (proportional integral derivative) control, are largely used in the industrial sector because of its robustness and because they are easy to be implemented. In this work, a data acquisition system was implemented for monitoring the most relevant process variables, like: both inlet and outlet drying air temperature, dryer rotation, outlet air speed and humidity, and mass of the final product. Openloop tests were realized to identify a mathematical model able to represent the drying process for the rotary system. From this model, a PID controller was tuned using a direct synthesis method, assuming a first order trajectory. The PID controller was implemented in the system in order to control the inlet drying air temperature. By the end, closedloop tests (operating in automatic mode) were realized to observe the controller performance, and, after setting the best tune, experiments were realized using passion fruit seeds as raw material. The experiments realized in closedloop showed a satisfactory performance by the implemented control strategy for the drying air temperature of the rotary system

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The proposed of scanning of an electrical industrial substation HV is associated with a segment of the Electrotechnical area and aims the study and preliminary application of digital technologies in the protection, control, measurement and automation maneuvers aimed at a Industrial Electrical System typical High Voltage. Well intended to supervision, protection and control of major electrical and thermal quantities involved in a substation, such as voltage levels, current, temperature, power factor, loads of transformers and circuit feeders, status of interlocking devices, switching equipment maneuvers, etc

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With the growth of the demand on electric energy in the last decades, the urban distribution and transmission systems have experienced a bigger necessity to improve on the substations, the automation procedures and techniques on the operation maneuvers of such systems, in a sense that better attends the quality levels, availability, continuity and operational reliability. In this way, the objective of the present paper is to perform a study of protection and control on an electrical industrial system involving the procedures of digitizing and maneuvers automatism utilizing operational techniques and other pertinent information used in a typical high-voltage Industrial Electrical System. Analysis were made on short-circuits to specify the main components of the 138 [kV] substation, in addition, there were used digital MiCOM relays to make the protection of the present elements. With that, a program was developed to allow the user to monitor the condition of circuit-breakers through a supervision screen being able to simulate some kinds of faults, as well as observing the characteristics of each device. This way, the importance of having a fast and reliable system that ensures the equipment’s protection and the industrial process continuity due to faults on the electrical system is noticeable. It’s important to highlight that all this digitizing was mainly favored by the development of digital technology on the last years, mainly on microelectronics, also with the appearance of supervision gadgets allowing the development of complex systems in supervision and electric energy control

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The increasing economic competition drives the industry to implement tools that improve their processes efficiencies. The process automation is one of these tools, and the Real Time Optimization (RTO) is an automation methodology that considers economic aspects to update the process control in accordance with market prices and disturbances. Basically, RTO uses a steady-state phenomenological model to predict the process behavior, and then, optimizes an economic objective function subject to this model. Although largely implemented in industry, there is not a general agreement about the benefits of implementing RTO due to some limitations discussed in the present work: structural plant/model mismatch, identifiability issues and low frequency of set points update. Some alternative RTO approaches have been proposed in literature to handle the problem of structural plant/model mismatch. However, there is not a sensible comparison evaluating the scope and limitations of these RTO approaches under different aspects. For this reason, the classical two-step method is compared to more recently derivative-based methods (Modifier Adaptation, Integrated System Optimization and Parameter estimation, and Sufficient Conditions of Feasibility and Optimality) using a Monte Carlo methodology. The results of this comparison show that the classical RTO method is consistent, providing a model flexible enough to represent the process topology, a parameter estimation method appropriate to handle measurement noise characteristics and a method to improve the sample information quality. At each iteration, the RTO methodology updates some key parameter of the model, where it is possible to observe identifiability issues caused by lack of measurements and measurement noise, resulting in bad prediction ability. Therefore, four different parameter estimation approaches (Rotational Discrimination, Automatic Selection and Parameter estimation, Reparametrization via Differential Geometry and classical nonlinear Least Square) are evaluated with respect to their prediction accuracy, robustness and speed. The results show that the Rotational Discrimination method is the most suitable to be implemented in a RTO framework, since it requires less a priori information, it is simple to be implemented and avoid the overfitting caused by the Least Square method. The third RTO drawback discussed in the present thesis is the low frequency of set points update, this problem increases the period in which the process operates at suboptimum conditions. An alternative to handle this problem is proposed in this thesis, by integrating the classic RTO and Self-Optimizing control (SOC) using a new Model Predictive Control strategy. The new approach demonstrates that it is possible to reduce the problem of low frequency of set points updates, improving the economic performance. Finally, the practical aspects of the RTO implementation are carried out in an industrial case study, a Vapor Recompression Distillation (VRD) process located in Paulínea refinery from Petrobras. The conclusions of this study suggest that the model parameters are successfully estimated by the Rotational Discrimination method; the RTO is able to improve the process profit in about 3%, equivalent to 2 million dollars per year; and the integration of SOC and RTO may be an interesting control alternative for the VRD process.

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