基于数据驱动的轴流压气机特性图规律及预测

Translated title of the contribution: Laws and prediction of axial compressor performance map based on data-driven

Tantao Liu, Limin Gao, Xudong Feng

Research output: Contribution to journalArticlepeer-review

Abstract

To explore the inherent laws of axial compressors' performance maps, more than 50 axial compressors' characteristic data were studied based on data analysis and thermodynamic principle. By introducing a variety of thermodynamic parameters into the performance curves and novel performance parameters, the research of laws between physics quantities of compressors was performed from three aspects which were peak efficiency lines, near-surge zones and near-stall zones. The relationship between compressor characteristic parameters and design indicators was found and the prediction algorithm was developed to predict the performance of compressors based on design indicators and performance parameters. It showed that there was a linear relationship between thermodynamics parameters within working speed range. The performance parameters of compressors were obviously correlated with design total pressure ratio and little correlated with design efficiency. The prediction algorithm can predict the performance map of compressors (total pressure ratio less than 8) well just relying on the design indicators and performance parameters without blades geometry information.

Translated title of the contributionLaws and prediction of axial compressor performance map based on data-driven
Original languageChinese (Traditional)
Pages (from-to)1072-1082
Number of pages11
JournalHangkong Dongli Xuebao/Journal of Aerospace Power
Volume36
Issue number5
DOIs
StatePublished - May 2021

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