Title of article
Neural Network Modeling For Main Steam Temperature System
Author/Authors
Mazalan, N. A. Universiti Teknologi Malaysia - Faculty of Mechanical Engineering, Malaysia , Malek, A. A. Malakoff Corporation Berhad, Malaysia , Wahid, Mazlan A. Universiti Teknologi Malaysia - FKM - High Speed Reacting Flow Laboratory (HiREF), Department of Thermofluids, Malaysia , Mailah, M. Universiti Teknologi Malaysia - Faculty of Mechanical Engineering, Malaysia
From page
93
To page
97
Abstract
Main Steam Temperature (MST) is non-linear, large inertia, long dead time and load dependant parameters. The paper present MST modeling method using actual plant data by utilizing MATLAB s Neural Network toolbox. The result of the simulation showed the MST model based on actual plant data is possible but the raw data need to be pre-processed for better output. Generator output, total main steam flow, main steam pressure and total spray flow are four main parameters affected the behavior of MST in coal fired power plant boiler.
Keywords
Main steam temperature , neural network , coal fired power plant
Journal title
Jurnal Teknologi :F
Journal title
Jurnal Teknologi :F
Record number
2716549
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