On-line condition monitoring system for high level trip water in steam Boiler's Drum

Firas B.Ismail Alnaimi, Marwan A Ali, Hussain H. Al-Kayiem, Khairul Salleh Bin Mohamed Sahari

Research output: Contribution to journalConference article

Abstract

This paper presents a monitoring technique using Artificial Neural Networks (ANN) with four different training algorithms for high level water in steam boiler's drum. Four Back-Propagations neural networks multidimensional minimization algorithms have been utilized. Real time data were recorded from power plant located in Malaysia. The developed relevant variables were selected based on a combination of theory, experience and execution phases of the model. The Root Mean Square (RMS) Error has been used to compare the results of one and two hidden layer (1HL), (2HL) ANN structures.

Original languageEnglish
Article number03011
JournalMATEC Web of Conferences
Volume13
DOIs
Publication statusPublished - 01 Jan 2014
Event4th International Conference on Production, Energy and Reliability, ICPER 2014 - Kuala Lumpur, Malaysia
Duration: 03 Jun 201405 Jun 2014

All Science Journal Classification (ASJC) codes

  • Chemistry(all)
  • Materials Science(all)
  • Engineering(all)

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