994 resultados para PLC automation


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A concepção de instalações eléctricas deve garantir condições de segurança para as pessoas e equipamentos. Para tal é exigida, quer por força de regulamentação ou de normalização, a instalação de dispositivos que garantam a detecção e a protecção contra os defeitos mais comuns nas instalações eléctricas como, por exemplo, as sobreintensidades e as sobretensões. Susceptíveis de criar sobretensões perigosas nas instalações eléctricas, as descargas atmosféricas podem ainda causar danos estruturais elevados, o que, em algumas actividades económicas, torna fundamental a implementação de medidas de protecção contra este fenómeno natural. A protecção contra descargas atmosféricas directas consiste em identificar as vulnerabilidades das estruturas e, nesses locais, implementar dispositivos de captura, direccionamento e escoamento da descarga atmosférica à terra, em condições de segurança. O presente trabalho, desenvolvido no âmbito da dissertação de Mestrado em Engenharia Electrotécnica, visa desenvolver e implementar uma ferramenta computacional, baseada em programas de desenho assistido por computador (CAD) de utilização corrente na área de projecto de arquitectura e de engenharia, que permita, no âmbito de normas internacionais, a análise e implementação de sistemas de protecção em edifícios contra descargas atmosféricas de uma forma rápida e expedita. Baseado num programa CAD 3D, que permite a modelização tridimensional das estruturas a proteger, a ferramenta desenvolvida tentará identificar as suas vulnerabilidades das estruturas às descargas atmosféricas directas, com o intuito de implementar as medidas de protecção mais adequadas do ponto de vista técnico económico. Prevê-se que a ferramenta resultante deste estudo, o Simulador do Modelo Electrogeométrico (SIMODEL), possibilite aos projectistas e particularmente aos alunos das unidades curriculares na área do projecto de instalações eléctricas da Área Departamental de Engenharia de Sistemas e Potencia e Automação (ADESPA) do ISEL, estudar e implementar sistemas de protecção contra descargas atmosféricas (SPDA) baseados na normalização internacional do CENELEC e da IEC, nomeadamente as normas da série 62305.

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Nowadays, the cooperative intelligent transport systems are part of a largest system. Transportations are modal operations integrated in logistics and, logistics is the main process of the supply chain management. The supply chain strategic management as a simultaneous local and global value chain is a collaborative/cooperative organization of stakeholders, many times in co-opetition, to perform a service to the customers respecting the time, place, price and quality levels. The transportation, like other logistics operations must add value, which is achieved in this case through compression lead times and order fulfillments. The complex supplier's network and the distribution channels must be efficient and the integral visibility (monitoring and tracing) of supply chain is a significant source of competitive advantage. Nowadays, the competition is not discussed between companies but among supply chains. This paper aims to evidence the current and emerging manufacturing and logistics system challenges as a new field of opportunities for the automation and control systems research community. Furthermore, the paper forecasts the use of radio frequency identification (RFID) technologies integrated into an information and communication technologies (ICT) framework based on distributed artificial intelligence (DAI) supported by a multi-agent system (MAS), as the most value advantage of supply chain management (SCM) in a cooperative intelligent logistics systems. Logistical platforms (production or distribution) as nodes of added value of supplying and distribution networks are proposed as critical points of the visibility of the inventory, where these technological needs are more evident.

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Na sociedade atual existe uma necessidade crescente, por parte de pessoas com incapacidades motoras, de utilizarem meios adaptados que lhes permita serem mais autónomos e menos limitados. Para isso, têm sido desenvolvidos constantemente melhores acessibilidades aos transportes, oferecendo a esta população melhores condições. Neste sentido, e em colaboração com a Câmara Municipal de Lisboa (C.M.L.), a realização deste trabalho de projeto teve como fundamento a necessidade de desenvolver uma nova viatura adaptada para transporte de deficientes motores, com o objetivo de acompanhar o mercado e de renovar a frota já existente. Além disso, algumas das viaturas em funcionamento nos serviços da C.M.L. já se encontravam obsoletas, não oferecendo totais condições de segurança aos passageiros, pois eram utilizados bancos corridos para dois passageiros; os degraus de acesso da porta lateral não ofereciam a máxima segurança; e algumas plataformas não apresentavam capacidade para elevação de cadeiras de rodas elétricas. As soluções encontradas para a nova viatura foram: aplicação de uma plataforma eletrohidráulica do tipo “gaveta”, para que ficasse perfeitamente arrumada; sobrelevação do piso interior da viatura para permitir arrumação da plataforma; instalação de bancos unitários, com rotação de 90 graus, para facilitar a entrada de cadeiras de rodas e oferecer mais espaço ao habitáculo; e realização do dimensionamento do circuito óleo-hidráulico da estrutura de elevação traseira (plataforma) para permitir a elevação de cadeiras de rodas elétricas. Neste trabalho foram utilizados vários programas informáticos de engenharia como o SolidWorks® e ANSYS® para o cálculo estrutural e o Automation Studio® para simulação do funcionamento do circuito óleo-hidráulico. A nova viatura desenvolvida serviu para substituir uma das mais antigas, tendo a C.M.L. neste momento uma adaptação inovadora, que respeita todas as necessidades e especificações requeridas.

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A definition of medium voltage (MV) load diagrams was made, based on the data base knowledge discovery process. Clustering techniques were used as support for the agents of the electric power retail markets to obtain specific knowledge of their customers’ consumption habits. Each customer class resulting from the clustering operation is represented by its load diagram. The Two-step clustering algorithm and the WEACS approach based on evidence accumulation (EAC) were applied to an electricity consumption data from a utility client’s database in order to form the customer’s classes and to find a set of representative consumption patterns. The WEACS approach is a clustering ensemble combination approach that uses subsampling and that weights differently the partitions in the co-association matrix. As a complementary step to the WEACS approach, all the final data partitions produced by the different variations of the method are combined and the Ward Link algorithm is used to obtain the final data partition. Experiment results showed that WEACS approach led to better accuracy than many other clustering approaches. In this paper the WEACS approach separates better the customer’s population than Two-step clustering algorithm.

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Scheduling is a critical function that is present throughout many industries and applications. A great need exists for developing scheduling approaches that can be applied to a number of different scheduling problems with significant impact on performance of business organizations. A challenge is emerging in the design of scheduling support systems for manufacturing environments where dynamic adaptation and optimization become increasingly important. In this paper, we describe a Self-Optimizing Mechanism for Scheduling System through Nature Inspired Optimization Techniques (NIT).

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This chapter addresses the resolution of dynamic scheduling by means of meta-heuristic and multi-agent systems. Scheduling is an important aspect of automation in manufacturing systems. Several contributions have been proposed, but the problem is far from being solved satisfactorily, especially if scheduling concerns real world applications. The proposed multi-agent scheduling system assumes the existence of several resource agents (which are decision-making entities based on meta-heuristics) distributed inside the manufacturing system that interact with other agents in order to obtain optimal or near-optimal global performances.

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In this paper we present VERITAS, a tool that focus time maintenance, that is one of the most important processes in the engineering of the time during the development of KBS. The verification and validation (V&V) process is part of a wider process denominated knowledge maintenance, in which an enterprise systematically gathers, organizes, shares, and analyzes knowledge to accomplish its goals and mission. The V&V process states if the software requirements specifications have been correctly and completely fulfilled. The methodologies proposed in software engineering have showed to be inadequate for Knowledge Based Systems (KBS) validation and verification, since KBS present some particular characteristics. VERITAS is an automatic tool developed for KBS verification which is able to detect a large number of knowledge anomalies. It addresses many relevant aspects considered in real applications, like the usage of rule triggering selection mechanisms and temporal reasoning.

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Power system planning, control and operation require an adequate use of existing resources as to increase system efficiency. The use of optimal solutions in power systems allows huge savings stressing the need of adequate optimization and control methods. These must be able to solve the envisaged optimization problems in time scales compatible with operational requirements. Power systems are complex, uncertain and changing environments that make the use of traditional optimization methodologies impracticable in most real situations. Computational intelligence methods present good characteristics to address this kind of problems and have already proved to be efficient for very diverse power system optimization problems. Evolutionary computation, fuzzy systems, swarm intelligence, artificial immune systems, neural networks, and hybrid approaches are presently seen as the most adequate methodologies to address several planning, control and operation problems in power systems. Future power systems, with intensive use of distributed generation and electricity market liberalization increase power systems complexity and bring huge challenges to the forefront of the power industry. Decentralized intelligence and decision making requires more effective optimization and control techniques techniques so that the involved players can make the most adequate use of existing resources in the new context. The application of computational intelligence methods to deal with several problems of future power systems is presented in this chapter. Four different applications are presented to illustrate the promises of computational intelligence, and illustrate their potentials.

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In the context of electricity markets, transmission pricing is an important tool to achieve an efficient operation of the electricity system. The electricity market is influenced by several factors; however the transmission network management is one of the most important aspects, because the network is a natural monopoly. The transmission tariffs can help to regulate the market, for this reason transmission tariffs must follow strict criteria. This paper presents the following methods to tariff the use of transmission networks by electricity market players: Post-Stamp Method; MW-Mile Method Distribution Factors Methods; Tracing Methodology; Bialek’s Tracing Method and Locational Marginal Price. A nine bus transmission network is used to illustrate the application of the tariff methods.

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This paper introduces the PCMAT platform project and, in particular, one of its components, the PCMAT Metadata Authoring Tool. This is an educational web application that allows the project metadata creators to write the metadata associated to each learning object without any concern for the metadata schema semantics. Furthermore it permits the project managers to add or delete elements to the schema, without having to rewrite or compile any code.

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This paper presents the proposal of an architecture for developing systems that interact with Ambient Intelligence (AmI) environments. This architecture has been proposed as a consequence of a methodology for the inclusion of Artificial Intelligence in AmI environments (ISyRAmI - Intelligent Systems Research for Ambient Intelligence). The ISyRAmI architecture considers several modules. The first is related with the acquisition of data, information and even knowledge. This data/information knowledge deals with our AmI environment and can be acquired in different ways (from raw sensors, from the web, from experts). The second module is related with the storage, conversion, and handling of the data/information knowledge. It is understood that incorrectness, incompleteness, and uncertainty are present in the data/information/knowledge. The third module is related with the intelligent operation on the data/information/knowledge of our AmI environment. Here we include knowledge discovery systems, expert systems, planning, multi-agent systems, simulation, optimization, etc. The last module is related with the actuation in the AmI environment, by means of automation, robots, intelligent agents and users.

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The Bologna Process aimed to build a European Higher Education Area promoting student's mobility. The adoption of Bologna Declaration directives requires a self management distributed approach to deal with student's mobility, allowing frequent updates in institutions rules or legislation. This paper suggests a computational system architecture, which follows a social network design. A set of structured annotations is proposed in order to organize the user's information. For instance, when the user is a student its annotations are organized into an academic record. The academic record data is used to discover interests, namely mobility interests, among students that belongs the academic network. These ideas have been applied into a demonstrator that includes a mobility simulator to compare and show the student's academic evolution.

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Mestrado em Engenharia Electrotécnica – Sistemas Eléctricos de Energia

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Projecto apresentado ao Instituto Politécnico do Porto para obtenção do Grau de Mestre em Logística Orientada por Prof. Doutor Gouveia

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Liver steatosis is a common disease usually associated with social and genetic factors. Early detection and quantification is important since it can evolve to cirrhosis. In this paper, a new computer-aided diagnosis (CAD) system for steatosis classification, in a local and global basis, is presented. Bayes factor is computed from objective ultrasound textural features extracted from the liver parenchyma. The goal is to develop a CAD screening tool, to help in the steatosis detection. Results showed an accuracy of 93.33%, with a sensitivity of 94.59% and specificity of 92.11%, using the Bayes classifier. The proposed CAD system is a suitable graphical display for steatosis classification.