Spelling suggestions: "subject:"inferential system"" "subject:"nferential system""
1 |
Sistema H?brido de Infer?ncia Baseado em An?lise de Componentes Principais e Redes Neurais Artificiais Aplicado a Plantas de Processamento de G?s NaturalLinhares, Leandro Luttiane da Silva 19 March 2010 (has links)
Made available in DSpace on 2014-12-17T14:55:42Z (GMT). No. of bitstreams: 1
LeandroLSL_DISSERT.pdf: 1890433 bytes, checksum: 540cbd4cf39fb3515249b7cecd6d0dcc (MD5)
Previous issue date: 2010-03-19 / Conselho Nacional de Desenvolvimento Cient?fico e Tecnol?gico / Nowadays, where the market competition requires products with better quality and a constant search for cost savings and a better use of raw materials, the research for more efficient control strategies becomes vital. In Natural Gas Processin Units (NGPUs), as in the most chemical processes, the quality control is accomplished through their products composition. However, the chemical composition analysis has a long measurement time,
even when performed by instruments such as gas chromatographs. This fact hinders the development of control strategies to provide a better process yield. The natural gas processing is one of the most important activities in the petroleum industry. The main economic product of a NGPU is the liquefied petroleum gas (LPG). The LPG is ideally composed by propane and butane, however, in practice, its composition has some contaminants, such as ethane and pentane. In this work is proposed an inferential system using neural networks to estimate the ethane and pentane mole fractions in LPG and the propane mole fraction in residual gas. The goal is to provide the values of these estimated variables in every minute using a single multilayer neural network, making it possibly to apply inferential control techniques in order to monitor the LPG quality and to reduce the propane loss in the process. To develop this work a NGPU was simulated in HYSYS R software, composed by two distillation collumns: deethanizer and debutanizer. The inference is performed through the process variables of the PID controllers present in the instrumentation of these columns. To reduce the complexity of the inferential neural network is used the statistical technique of principal component analysis to decrease the number of network inputs, thus forming a hybrid inferential system. It is also proposed in this work a simple strategy to correct the inferential system in real-time, based on measurements of the chromatographs which may exist in process under study / Nos dias atuais, em que a concorr?ncia de mercado exige produtos de melhor qualidade e a busca constante pela redu??o de custos e pelo melhor aproveitamento das mat?rias-primas, a utiliza??o de estrat?gias de controle mais eficientes torna-se fundamental. Nas Unidades de Processamento de G?s Natural (UPGNs), assim como na maioria dos processos qu?micos, o controle de qualidade ? realizado a partir da composi??o de
seus produtos. Entretanto, a an?lise de composi??es qu?micas, mesmo quando realizada por equipamentos como os cromat?grafos a g?s, apresenta longos intervalos de medi??o.
Esse fato dificulta a elabora??o de estrat?gias de controle que proporcionem um melhor rendimento do processo. Geralmente, o principal produto econ?mico de uma UPGN ? o GLP (G?s Liquefeito de Petr?leo). Outros produtos comumente obtidos nessas unidades s?o a gasolina natural e o g?s residual. O GLP ? formado idealmente por propano e butano. Entretanto, na pr?tica, apresenta em sua composi??o contaminantes, tais como o etano e o pentano. Neste trabalho ? proposto um sistema de infer?ncia utilizando redes neurais para estimar as
fra??es molares de etano e pentano no GLP e a fra??o molar de propano no g?s residual. O objetivo ? estimar essas vari?veis a cada minuto com uma ?nica rede neural de m?ltiplas camadas, permitindo a aplica??o de t?cnicas de controle inferencial visando a controlar a qualidade do GLP e reduzir a perda de propano no processo. No desenvolvimento deste trabalho, ? simulada no software HYSYS R uma UPGN formada por uma coluna de destila??o deetanizadora e outra debutanizadora. A infer?ncia ? realizada a partir das vari?veis de processo de alguns controladores PID presentes na instrumenta??o das colunas citadas. Com o intuito de reduzir a complexidade da rede
neural de infer?ncia, ? utilizada a t?cnica estat?stica de an?lise de componentes principais (ACP) para diminuir o n?mero de entradas da rede. Tem-se, portanto, um sistema h?brido de infer?ncia. Tamb?m ? proposta neste trabalho, uma estrat?gia simples para a corre??o em tempo real do sistema de infer?ncia, tendo como base as medi??es dos poss?veis cromat?grafos
de linha presentes no processo em estudo
|
2 |
Aplikace fuzzy logiky při hodnocení dodavatelů firmy / The Application of Fuzzy Logic for Rating of Suppliers for the FirmZegzulka, Ivo January 2014 (has links)
This thesis deals with the design of fuzzy system that can evaluate supplier of spare parts for service. The result should be applicable to a company Iveta Šťastníková - car and tire service. Primarily it should simplify operations associated with the selection of appropriate spare parts, tools and other equipment needed to operate with car service station. First, we introduce the theoretical basis for the paper, and then we go to the present state and the analysis itself. The result is a proposed solution which should correspond to the needs of the owner.
|
Page generated in 0.0857 seconds