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A Performance Evaluation Method of Coal-Fired Boiler Based on Neural Network

  • Yingyue ChenEmail author
  • Lijun Xiao
  • Osama Hosam
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11910)

Abstract

According to the evaluation and control of energy-saving and emission reduction performance of coal-fired boilers, the performance indexes of boiler combustion and emissions were studied, and a performance evaluation and control method based on neural network was proposed. Firstly, the influencing factors of boiler combustion emission are analyzed. A boiler combustion emission evaluation model based on AdaBoost-BP algorithm is designed. The model is trained and tested by coal-fired power plant data and national emission standards, and the principal component analysis method is adopted. The core parameters are adjusted to get the best control solution. Finally, experiments show that the model and method have better advantages in comparison with similar methods.

Keywords

Coal-fired boiler Emission Neural network Performance evaluation Control 

Notes

Acknowledgements

This work is supported by the Social Science Planning Project in Fujian Province Project (FJ2016C133), the Scientific Research Foundation for Young and Middle-aged Teachers of Fujian Province (JZ160163) and the Fujian Province Education Science “13th Five-Year Plan” Project (FJJKCG16-289).

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.The School of Economic and ManagementXiamen University of TechnologyXiamenChina
  2. 2.The Department of AccountingGuangzhou College of Technology and BusinessGuangzhouChina
  3. 3.The College of Computer Science and Engineering CollegeSaudi Arabia UniversityRiyadhSaudi Arabia

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