Monitoring of a thermoelectric power plant based on multivariate statistical process control

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dc.creatorJoyce M. F. Fonseca
dc.creatorBruno M. Sousa
dc.creatorWebber E. Aguiar
dc.creatorAnisio R. Braga
dc.creatorAndré P. Lemos
dc.creatorHugo C. C. Michel
dc.creatorCarmela Maria Polito Braga
dc.date.accessioned2025-03-19T16:02:38Z
dc.date.accessioned2025-09-09T01:20:56Z
dc.date.available2025-03-19T16:02:38Z
dc.date.issued2016
dc.identifier.doi10.1109/EAIS.2016.7502371
dc.identifier.isbn978-1-5090-2583-1
dc.identifier.issn2473-4691
dc.identifier.urihttps://hdl.handle.net/1843/80763
dc.languageeng
dc.publisherUniversidade Federal de Minas Gerais
dc.rightsAcesso Restrito
dc.subjectHuman-computer interaction
dc.subjectIntelligent agents (Computer software)
dc.subjectUsinas elétricas
dc.subjectTermoeletricidade
dc.subjectControle de processo - Métodos estatísticos
dc.subject.otherboiler
dc.subject.otherturbine-generator
dc.subject.otherPCA - PIMS
dc.subject.otherHotelling?s T2 chart
dc.subject.otherStatistical Control
dc.subject.otherThermoelectric Power Plants
dc.subject.otherMultivariate Control
dc.subject.otherComplex Systems
dc.subject.otherAdaptive Estimation
dc.subject.otherProcessing Technology
dc.subject.otherNatural Gas
dc.subject.otherEigenvectors of Matrix
dc.subject.otherHotelling T2
dc.subject.otherXML File
dc.subject.otherLow Calorific Value
dc.subject.otherBlast Furnace
dc.subject.otherPrincipal Component Scores
dc.subject.otherDecentralized Control
dc.titleMonitoring of a thermoelectric power plant based on multivariate statistical process control
dc.typeArtigo de evento
local.citation.epage56
local.citation.spage49
local.description.resumoThermoelectric power plants have critical units, such as the boiler and the turbine-generator, which are complex multivariate systems. These units exhibit non-stationary behavior and multiple operational modes that imply constant changes of set points of key performance variables. A methodology based on MSPC (Multivariate Statistical Process Control) techniques and PCA (Principal Component Analysis) is presented with an adaptive mean estimator that deals with frequent changes of set points, both for design and just in time monitoring. The proposed methodology is implemented in a thermoelectric power plant using a commercial PIMS (Process Information Management System) software suite. Experimental results illustrate and validate the proposition, its just-in-time implementation and usage.
local.publisher.countryBrasil
local.publisher.departmentENG - DEPARTAMENTO DE ENGENHARIA ELETRÔNICA
local.publisher.initialsUFMG
local.url.externahttps://ieeexplore.ieee.org/document/7502371

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