Early Diagnosis of Combustion Instability Using Statistical Methods

Seungkyu Choi; Jaemin Baek; Daesik Kim

doi:10.15231/jksc.2022.27.3.001

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2022 Vol.27, Issue 3 Next Page

Research Article

Early Diagnosis of Combustion Instability Using Statistical Methods 통계적 기법을 활용한 연소불안정 조기진단

30 September 2022. pp. 1-7

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Abstract

Various statistical approaches have been recently proposed to detect combustion instabilities in a short time through a fast data processing on dynamic pressure of time domain measured in a gas turbine combustor. In the current study, four methods, PE(permutation entropy), TK(temporal kurtosis), ZCR(zero crossing rate), and STFT(short time Fourier transform), were applied and compared with the conventional instability onset-detection method, RMS(root mean square), using the same dynamic pressure data measured in a lab-scale gas turbine combustor. As a result of the comparison, it was found that PE, TK, and ZCR can detect combustion vibration earlier than the instability onset time determined by RMS. On the other hand, STFT did not show relatively good early detection characteristics.

Keywords

Combustion instability

Permutation entropy

Temporal kurtosis

Zero crossing rate

Short time Fourier transform

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Information

Publisher :The Korean Society Combustion
Publisher(Ko) :한국연소학회
Journal Title :Journal of The Korean Society Combustion
Journal Title(Ko) :한국연소학회지
Volume : 27
No :3
Pages :1-7
Received Date : 2022-06-07
Revised Date : 2022-06-21
Accepted Date : 2022-07-07
DOI :https://doi.org/10.15231/jksc.2022.27.3.001

Journal of The Korean Society CombustionISSN:1226-0959(Print) 2466-2089(Online)한국연소학회

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