Neural network modeling for main steam temperature system
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 po...
Saved in:
| Main Authors: | , , , |
|---|---|
| 格式: | Article |
| 語言: | English |
| 出版: |
Penerbit UTM
2014
|
| 主題: | |
| 在線閱讀: | http://eprints.utm.my/id/eprint/54230/1/NorA.Mazalan2014_Neuralnetworkmodelingformain.pdf http://eprints.utm.my/id/eprint/54230/ http://dx.doi.org/10.11113/jt.v69.3151 |
| 標簽: |
添加標簽
沒有標簽, 成為第一個標記此記錄!
|
| id |
my.utm.54230 |
|---|---|
| record_format |
eprints |
| spelling |
my.utm.542302018-08-03T08:50:47Z http://eprints.utm.my/id/eprint/54230/ Neural network modeling for main steam temperature system Mazalan, Nor A. A. Malek, Azlan Abdul Wahid, Mazlan Mailah, Musa TJ Mechanical engineering and machinery 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 Penerbit UTM 2014 Article PeerReviewed application/pdf en http://eprints.utm.my/id/eprint/54230/1/NorA.Mazalan2014_Neuralnetworkmodelingformain.pdf Mazalan, Nor A. and A. Malek, Azlan and Abdul Wahid, Mazlan and Mailah, Musa (2014) Neural network modeling for main steam temperature system. Jurnal Teknologi (Sciences and Engineering), 69 (3). pp. 93-97. ISSN 0127-9696 http://dx.doi.org/10.11113/jt.v69.3151 DOI: 10.11113/jt.v69.3151 |
| institution |
Universiti Teknologi Malaysia |
| building |
UTM Library |
| collection |
Institutional Repository |
| continent |
Asia |
| country |
Malaysia |
| content_provider |
Universiti Teknologi Malaysia |
| content_source |
UTM Institutional Repository |
| url_provider |
http://eprints.utm.my/ |
| language |
English |
| topic |
TJ Mechanical engineering and machinery |
| spellingShingle |
TJ Mechanical engineering and machinery Mazalan, Nor A. A. Malek, Azlan Abdul Wahid, Mazlan Mailah, Musa Neural network modeling for main steam temperature system |
| description |
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 |
| format |
Article |
| author |
Mazalan, Nor A. A. Malek, Azlan Abdul Wahid, Mazlan Mailah, Musa |
| author_facet |
Mazalan, Nor A. A. Malek, Azlan Abdul Wahid, Mazlan Mailah, Musa |
| author_sort |
Mazalan, Nor A. |
| title |
Neural network modeling for main steam temperature system |
| title_short |
Neural network modeling for main steam temperature system |
| title_full |
Neural network modeling for main steam temperature system |
| title_fullStr |
Neural network modeling for main steam temperature system |
| title_full_unstemmed |
Neural network modeling for main steam temperature system |
| title_sort |
neural network modeling for main steam temperature system |
| publisher |
Penerbit UTM |
| publishDate |
2014 |
| url |
http://eprints.utm.my/id/eprint/54230/1/NorA.Mazalan2014_Neuralnetworkmodelingformain.pdf http://eprints.utm.my/id/eprint/54230/ http://dx.doi.org/10.11113/jt.v69.3151 |
| _version_ |
1643653504241238016 |
| score |
13.251813 |