Monitoring of a thermoelectric power plant based on multivariate statistical process control
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Universidade Federal de Minas Gerais
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Thermoelectric 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.
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Human-computer interaction, Intelligent agents (Computer software), Usinas elétricas, Termoeletricidade, Controle de processo - Métodos estatísticos
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boiler, turbine-generator, PCA - PIMS, Hotelling?s T2 chart, Statistical Control, Thermoelectric Power Plants, Multivariate Control, Complex Systems, Adaptive Estimation, Processing Technology, Natural Gas, Eigenvectors of Matrix, Hotelling T2, XML File, Low Calorific Value, Blast Furnace, Principal Component Scores, Decentralized Control
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https://ieeexplore.ieee.org/document/7502371