Development and implementation of intelligent condition monitoring system for steam turbine trips
Sustainable initiatives are increasingly getting attention from the research community and one of the aspects in achieving sustainable development is to enhance the efficiency and optimize the technology used to generate and utilize energy. Fault detection and diagnosis is a critical optimization fa...
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Asian Research Publishing Network
2023
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my.uniten.dspace-229152023-05-29T14:13:22Z Development and implementation of intelligent condition monitoring system for steam turbine trips Alnaimi F.B.I. Ismail R.I.B. Ker P.J. 58027086700 57189236796 37461740800 Sustainable initiatives are increasingly getting attention from the research community and one of the aspects in achieving sustainable development is to enhance the efficiency and optimize the technology used to generate and utilize energy. Fault detection and diagnosis is a critical optimization factor in power generation sector. Early faults detection ensures that correct mitigation measures can be taken, whilst false alarms should be eschewed to avoid unnecessary cost of operation, interruption and downtime. Pure Intelligent Condition Monitoring System (ICMS) represented by artificial neural network (ANN), developed by training the network with real operational data, may be proven to be useful for realtime monitoring of a power plant. In this work, an integrated data preparation method has been proposed and the development of ANN models to detect steam turbine trip for Malaysia MNJ power station will be presented. Two models adopting feed forward with back propagation ANN were trained with real data from the MNJ station. The developed models were capable of detecting the specific trip within a period of 32 minutes before the actual trip occurrence, which is considered to provide good and satisfactory early fault detection. � 2006-2016 Asian Research Publishing Network (ARPN). All rights reserved. Final 2023-05-29T06:13:22Z 2023-05-29T06:13:22Z 2016 Article 2-s2.0-85009160454 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85009160454&partnerID=40&md5=3da3f8a8c6d986223d34717b4cd4fb0b https://irepository.uniten.edu.my/handle/123456789/22915 11 24 14275 14283 Asian Research Publishing Network Scopus |
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Sustainable initiatives are increasingly getting attention from the research community and one of the aspects in achieving sustainable development is to enhance the efficiency and optimize the technology used to generate and utilize energy. Fault detection and diagnosis is a critical optimization factor in power generation sector. Early faults detection ensures that correct mitigation measures can be taken, whilst false alarms should be eschewed to avoid unnecessary cost of operation, interruption and downtime. Pure Intelligent Condition Monitoring System (ICMS) represented by artificial neural network (ANN), developed by training the network with real operational data, may be proven to be useful for realtime monitoring of a power plant. In this work, an integrated data preparation method has been proposed and the development of ANN models to detect steam turbine trip for Malaysia MNJ power station will be presented. Two models adopting feed forward with back propagation ANN were trained with real data from the MNJ station. The developed models were capable of detecting the specific trip within a period of 32 minutes before the actual trip occurrence, which is considered to provide good and satisfactory early fault detection. � 2006-2016 Asian Research Publishing Network (ARPN). All rights reserved. |
| author2 |
58027086700 |
| author_facet |
58027086700 Alnaimi F.B.I. Ismail R.I.B. Ker P.J. |
| format |
Article |
| author |
Alnaimi F.B.I. Ismail R.I.B. Ker P.J. |
| spellingShingle |
Alnaimi F.B.I. Ismail R.I.B. Ker P.J. Development and implementation of intelligent condition monitoring system for steam turbine trips |
| author_sort |
Alnaimi F.B.I. |
| title |
Development and implementation of intelligent condition monitoring system for steam turbine trips |
| title_short |
Development and implementation of intelligent condition monitoring system for steam turbine trips |
| title_full |
Development and implementation of intelligent condition monitoring system for steam turbine trips |
| title_fullStr |
Development and implementation of intelligent condition monitoring system for steam turbine trips |
| title_full_unstemmed |
Development and implementation of intelligent condition monitoring system for steam turbine trips |
| title_sort |
development and implementation of intelligent condition monitoring system for steam turbine trips |
| publisher |
Asian Research Publishing Network |
| publishDate |
2023 |
| _version_ |
1806425857790574592 |
| score |
13.222552 |