1. bookVolume 22 (2022): Issue 3 (June 2022)
Journal Details
License
Format
Journal
eISSN
1335-8871
First Published
07 Mar 2008
Publication timeframe
6 times per year
Languages
English
access type Open Access

Review of Measurement Techniques of Hydrocarbon Flame Equivalence Ratio and Applications of Machine Learning

Published Online: 22 Apr 2022
Volume & Issue: Volume 22 (2022) - Issue 3 (June 2022)
Page range: 122 - 135
Received: 23 Dec 2021
Accepted: 28 Feb 2022
Journal Details
License
Format
Journal
eISSN
1335-8871
First Published
07 Mar 2008
Publication timeframe
6 times per year
Languages
English
Abstract

Flame combustion diagnostics is a technique that uses different methods to diagnose the flame combustion process and study its physical and chemical basis. As one of the most important parameters of the combustion process, the flame equivalence ratio has a significant influence on the entire flame combustion, especially on the combustion efficiency and the emission of pollutants. Therefore, the measurement of the flame equivalence ratio has a huge impact on efficient combustion and environment protection. In view of this, several effective measuring methods were proposed, which were based on the different characteristics of flames radicals such as spectral properties. With the rapid growth of machine learning, more and more scholars applied it in the combustion diagnostics due to the excellent ability to fit parameters. This paper presents a review of various measuring techniques of hydrocarbon flame equivalent ratio and the applications of machine learning in combustion diagnostics, finally making a brief comparison between different measuring methods.

Keywords

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