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Submitted
September 27, 2015
Accepted
September 27, 2015
Published
September 27, 2015
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Abstract

An improvement in the efficiency on converting fuel energy to useful thermal energy could result in significant fuel saving for industrial Sector. In this paper artificial intelligence concept using Artificial Neural Network (ANN) is used to predict the optimized excess air requirement using real time and calculated data. This work determines the excess air requirement for complete combustion corresponding to theoretical CO2 in flue gases and real-time values obtained from remote measurements of CO2

Keywords

ANN Flue gas Analysis Excess Air Control Boiler Efficiency Losses.

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Authors retain the copyright without restrictions for their published content in this journal. IJSRTM is a SHERPA ROMEO Journal. 

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This is an open-access article distributed under the terms of  Creative Commons License

 

How to Cite
Gopinath, A. S., & Babu, N. S. (2015). Prediction of Excess Air Requirement Using ANN for the Improvement of Boiler Efficiency. International Journal of Students’ Research in Technology & Management, 2(4), 149–152. Retrieved from https://mgesjournals.com/ijsrtm/article/view/128
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References

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