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Estimation of boiler's tubes life, Artificial Neural Networks approach / Murtadha F. Muhsen

The analysis of creep-damage processes is becoming more and more important in engineering practice due to the fact that the exploitation condition like temperature and pressure are increasing while the weight of the structure should decrease. In the same time the safety standards are increasing too....

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Main Author: F. Muhsen, Murtadha
Format: Article
Language:English
Published: Faculty of Mechanical Engineering (FKM) and UiTM Press 2011
Online Access:http://ir.uitm.edu.my/id/eprint/17584/2/AJ_MURTADHA%20F.%20MUHSEN%20JME%2011.pdf
http://ir.uitm.edu.my/id/eprint/17584/
https://jmeche.uitm.edu.my/
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spelling my.uitm.ir.175842019-11-11T03:44:16Z http://ir.uitm.edu.my/id/eprint/17584/ Estimation of boiler's tubes life, Artificial Neural Networks approach / Murtadha F. Muhsen F. Muhsen, Murtadha The analysis of creep-damage processes is becoming more and more important in engineering practice due to the fact that the exploitation condition like temperature and pressure are increasing while the weight of the structure should decrease. In the same time the safety standards are increasing too. The accuracy of the mechanical state estimation (stresses, strains and displacements) mainly depends on the introduced constitutive equations and on the chosen structural analysis model. This paper is devoted to the prediction of boiler s tube life using of Artificial Neural Network (ANN) technique. Training data used were obtained from Kapar power station technical reports. Predicted values of the remnant tube life were compared to the experimentally collected data to verify the success of the algorithm; average absolute error obtained was 1.667%. Results obtained show that the designed network is capable of predicting the remnant life of the boilers tube successfully. Predicting boilers tube life successfully presented using this method will help maintenance engineers to schedule preventive maintenance procedure in order to minimize maintenance cost and to prevent any consequences of disasters which may happen if the necessary precautions were not taken. Faculty of Mechanical Engineering (FKM) and UiTM Press 2011 Article PeerReviewed text en http://ir.uitm.edu.my/id/eprint/17584/2/AJ_MURTADHA%20F.%20MUHSEN%20JME%2011.pdf F. Muhsen, Murtadha (2011) Estimation of boiler's tubes life, Artificial Neural Networks approach / Murtadha F. Muhsen. Journal of Mechanical Engineering (JMechE), 8 (2). pp. 59-69. ISSN 1823-5514 ; 2550-164X https://jmeche.uitm.edu.my/
institution Universiti Teknologi Mara
building Tun Abdul Razak Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Mara
content_source UiTM Institutional Repository
url_provider http://ir.uitm.edu.my/
language English
description The analysis of creep-damage processes is becoming more and more important in engineering practice due to the fact that the exploitation condition like temperature and pressure are increasing while the weight of the structure should decrease. In the same time the safety standards are increasing too. The accuracy of the mechanical state estimation (stresses, strains and displacements) mainly depends on the introduced constitutive equations and on the chosen structural analysis model. This paper is devoted to the prediction of boiler s tube life using of Artificial Neural Network (ANN) technique. Training data used were obtained from Kapar power station technical reports. Predicted values of the remnant tube life were compared to the experimentally collected data to verify the success of the algorithm; average absolute error obtained was 1.667%. Results obtained show that the designed network is capable of predicting the remnant life of the boilers tube successfully. Predicting boilers tube life successfully presented using this method will help maintenance engineers to schedule preventive maintenance procedure in order to minimize maintenance cost and to prevent any consequences of disasters which may happen if the necessary precautions were not taken.
format Article
author F. Muhsen, Murtadha
spellingShingle F. Muhsen, Murtadha
Estimation of boiler's tubes life, Artificial Neural Networks approach / Murtadha F. Muhsen
author_facet F. Muhsen, Murtadha
author_sort F. Muhsen, Murtadha
title Estimation of boiler's tubes life, Artificial Neural Networks approach / Murtadha F. Muhsen
title_short Estimation of boiler's tubes life, Artificial Neural Networks approach / Murtadha F. Muhsen
title_full Estimation of boiler's tubes life, Artificial Neural Networks approach / Murtadha F. Muhsen
title_fullStr Estimation of boiler's tubes life, Artificial Neural Networks approach / Murtadha F. Muhsen
title_full_unstemmed Estimation of boiler's tubes life, Artificial Neural Networks approach / Murtadha F. Muhsen
title_sort estimation of boiler's tubes life, artificial neural networks approach / murtadha f. muhsen
publisher Faculty of Mechanical Engineering (FKM) and UiTM Press
publishDate 2011
url http://ir.uitm.edu.my/id/eprint/17584/2/AJ_MURTADHA%20F.%20MUHSEN%20JME%2011.pdf
http://ir.uitm.edu.my/id/eprint/17584/
https://jmeche.uitm.edu.my/
_version_ 1685648963312549888
score 13.211869

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