Coal-fired boiler fault prediction using artificial neural networks
Boiler fault is a critical issue in a coal-fired power plant due to its high temperature and high pressure characteristics. The complexity of boiler design increases the difficulty of fault investigation in a quick moment to avoid long duration shut-down. In this paper, a boiler fault prediction mod...
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Institute of Advanced Engineering and Science
2023
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| author | Nistah N.N.M. Lim K.H. Gopal L. Alnaimi F.B.I. |
| author2 | 57211211943 |
| author_facet | 57211211943 Nistah N.N.M. Lim K.H. Gopal L. Alnaimi F.B.I. |
| author_sort | Nistah N.N.M. |
| building | UNITEN Library |
| collection | Institutional Repository |
| content_provider | Universiti Tenaga Nasional |
| content_source | UNITEN Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | Boiler fault is a critical issue in a coal-fired power plant due to its high temperature and high pressure characteristics. The complexity of boiler design increases the difficulty of fault investigation in a quick moment to avoid long duration shut-down. In this paper, a boiler fault prediction model is proposed using artificial neural network. The key influential parameters analysis is carried out to identify its correlation with the performance of the boiler. The prediction model is developed to achieve the least misclassification rate and mean squared error. Artificial neural network is trained using a set of boiler operational parameters. Subsequenlty, the trained model is used to validate its prediction accuracy against actual fault value from a collected real plant data. With reference to the study and test results, two set of initial weights have been tested to verify the repeatability of the correct prediction. The results show that the artificial neural network implemented is able to provide an average of above 92% prediction rate of accuracy. Copyright � 2018 Institute of Advanced Engineering and Science. All rights reserved. |
| format | Article |
| id | my.uniten.dspace-23737 |
| institution | Universiti Tenaga Nasional |
| publishDate | 2023 |
| publisher | Institute of Advanced Engineering and Science |
| record_format | dspace |
| spelling | my.uniten.dspace-237372023-05-29T14:51:23Z Coal-fired boiler fault prediction using artificial neural networks Nistah N.N.M. Lim K.H. Gopal L. Alnaimi F.B.I. 57211211943 25031784300 26967678300 58027086700 Boiler fault is a critical issue in a coal-fired power plant due to its high temperature and high pressure characteristics. The complexity of boiler design increases the difficulty of fault investigation in a quick moment to avoid long duration shut-down. In this paper, a boiler fault prediction model is proposed using artificial neural network. The key influential parameters analysis is carried out to identify its correlation with the performance of the boiler. The prediction model is developed to achieve the least misclassification rate and mean squared error. Artificial neural network is trained using a set of boiler operational parameters. Subsequenlty, the trained model is used to validate its prediction accuracy against actual fault value from a collected real plant data. With reference to the study and test results, two set of initial weights have been tested to verify the repeatability of the correct prediction. The results show that the artificial neural network implemented is able to provide an average of above 92% prediction rate of accuracy. Copyright � 2018 Institute of Advanced Engineering and Science. All rights reserved. Final 2023-05-29T06:51:23Z 2023-05-29T06:51:23Z 2018 Article 10.11591/ijece.v8i4.pp2486-2493 2-s2.0-85049557496 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85049557496&doi=10.11591%2fijece.v8i4.pp2486-2493&partnerID=40&md5=e5d5a7748c1121c14cb8475929476b2e https://irepository.uniten.edu.my/handle/123456789/23737 8 4 2486 2493 All Open Access, Hybrid Gold, Green Institute of Advanced Engineering and Science Scopus |
| spellingShingle | Nistah N.N.M. Lim K.H. Gopal L. Alnaimi F.B.I. Coal-fired boiler fault prediction using artificial neural networks |
| title | Coal-fired boiler fault prediction using artificial neural networks |
| title_full | Coal-fired boiler fault prediction using artificial neural networks |
| title_fullStr | Coal-fired boiler fault prediction using artificial neural networks |
| title_full_unstemmed | Coal-fired boiler fault prediction using artificial neural networks |
| title_short | Coal-fired boiler fault prediction using artificial neural networks |
| title_sort | coal-fired boiler fault prediction using artificial neural networks |
| url_provider | http://dspace.uniten.edu.my/ |