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Online coal calorific value prediction from mutiband coal/air combustion radiation characteristics

  • Beihang University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

A SVR modeling based online coal calorific value prediction method was introduced. Through wavelet transform and PCS process, coal flame radiation characteristics were extracted. Through SVR modeling, relationship model between radiation characteristic variables and coal calorific value was established. Proper SVR construction parameters were chosen through grid computing. Experiment results showed good coherence between SVR model prediction and laboratory results of coal calorific value. Proposed SVR based system relies on low cost multiband photoelectric sensors, which is easy to be installed at production spot, while satisfying system performance could meet practical needs of online operation adjusting to enhance production efficiency and diminish pollutant emissions.

Original languageEnglish
Title of host publication2012 the 8th IEEE International Symposium on Instrumentation and Control Technology, ISICT 2012 - Proceedings
Pages309-313
Number of pages5
DOIs
StatePublished - 2012
Event8th IEEE International Symposium on Instrumentation and Control Technology, ISICT 2012 - London, United Kingdom
Duration: 11 Jul 201213 Jul 2012

Publication series

Name2012 the 8th IEEE International Symposium on Instrumentation and Control Technology, ISICT 2012 - Proceedings

Conference

Conference8th IEEE International Symposium on Instrumentation and Control Technology, ISICT 2012
Country/TerritoryUnited Kingdom
CityLondon
Period11/07/1213/07/12

Keywords

  • PCA
  • SVR
  • coal calorific value
  • multiband photoelectric sensors

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