| Citation: | ZHEN Man, DONG Xuezhi, LIU Xiyang, et al. Physically enhanced prediction method of extrapolating low speed characteristics of compressor based on PSO-SVR[J]. Journal of Aerospace Power, 2025, 40（X）：20230303 doi: 10.13224/j.cnki.jasp.20230303
|
A physically enhanced prediction method based on particle swarm optimization (PSO) optimization support vector regression (SVR) was proposed to address the issue of low accuracy and discontinuous isentropic efficiency of compressor performance at low speed. This method combined several physical extrapolation methods and utilized particle swarm optimization to optimize the support vector regression model parameters for the regression prediction of compressor’s low speed characteristics. The traditional single-stage characteristic parameters of the compressor were converted into corrected torque, and the compressor zero speed characteristic line was extrapolated. The high-speed characteristics were employed as the training set to establish the support vector regression model, PSO was used to obtain the high-precision regression SVR model, and the model was applied to predict the low speed characteristics of compressor. Results showed that the minimum determination coefficient was 0.976, the maximum mean square error was 0.06%, and the maximum average relative error was 8.96% in the prediction results based on PSO-SVR model. The three working states of compressor were predicted at low speed based on PSO-SVR model, including compressor, stirrer and turbine states. Therefore, the prediction method can fully mine the information contained in the data, improve the prediction accuracy of compressor at low-speed characteristics and provide data support for engine starting simulation.
| [1] |
JONES G,PILIDIS P,CURNOCK B. Extrapolation of compressor characteristics to the low-speed region for sub-idle performance modelling[C]//Proceedings of ASME Turbo Expo. Amsterdam,The Netherlands: ASME,2002: 30649.
|
| [2] |
施洋,屠秋野,严红明,等. 一种航空发动机全状态性能模型[J]. 航空动力学报,2017,32(2): 373-381. SHI Yang,TU Qiuye,YAN Hongming,et al. A full states performance model for aero engine[J]. Journal of Aerospace Power,2017,32(2): 373-381. (in Chinese
SHI Yang, TU Qiuye, YAN Hongming, et al. A full states performance model for aero engine[J]. Journal of Aerospace Power, 2017, 32(2): 373-381. (in Chinese)
|
| [3] |
WANG Zhitao,LI Yiguang,MENG Hui,et al. Method of extrapolating low speed compressor curves based on improved similarity laws[C]//Proceedings of ASME Turbo Expo 2015: Turbine Technical Conference and Exposition,Montreal,Canada: ASME,2015: 44108.
|
| [4] |
郑绪生. 某型涡轴发动机起动建模技术研究[D]. 南京: 南京航空航天大学,2005. ZHENG Xusheng. Research on starting modeling technology of a turboshaft engine[D]. Nanjing: Nanjing University of Aeronautics and Astronautics,2005. (in Chinese
ZHENG Xusheng. Research on starting modeling technology of a turboshaft engine[D]. Nanjing: Nanjing University of Aeronautics and Astronautics, 2005. (in Chinese)
|
| [5] |
AGRAWAL R K,YUNIS M. A generalized mathematical model to estimate gas turbine starting characteristics[J]. Journal of Engineering for Power,1982,104(1): 194-201.
|
| [6] |
SEXTON W R. A method to control turbofan engine staring by varying compressor surge valve bleed[D]. Blacksburg,US: Virginia Polytechnic Institute and State University,2001.
|
| [7] |
郝旺,王占学,张晓博,等. 变循环发动机地面起动建模及控制规律设计方法[J]. 航空动力学报,2022,37(1): 152-164. HAO Wang,WANG Zhanxue,ZHANG Xiaobo,et al. Ground starting modeling and control law design method of variable cycle engine[J]. Journal of Aerospace Power,2022,37(1): 152-164. (in Chinese
HAO Wang, WANG Zhanxue, ZHANG Xiaobo, et al. Ground starting modeling and control law design method of variable cycle engine[J]. Journal of Aerospace Power, 2022, 37(1): 152-164. (in Chinese)
|
| [8] |
GUAN Cong,THEOTOKATOS G,ZHOU Peilin,et al. Computational investigation of a large containership propulsion engine operation at slow steaming conditions[J]. Applied Energy,2014,130: 370-383.
|
| [9] |
JOHNSEN I,BULLOCK R. Aerodynamic design of axial-flow compressors: NASA SP-36[R]. Ohio,US: NASA,1979.
|
| [10] |
STEINKE R J. A computer code for predicting multistage axial flow compressor performance by a meanline stage stacking method: NASA-TP-2020 [R]. Ohio,US: NASA,1982.
|
| [11] |
KURZKE J. SmoothC 8.3 user’s manual[M]. Aachen,Germany: GasTurb GmbH,2015.
|
| [12] |
KURZKE J,MARIE D W. Generating compressor maps to simulate starting and windmilling[C]//Proceedings of International Symposium of Air Breathing Engine,Canberra: ISABE,2019: 24299.
|
| [13] |
KURZKE J. How to get component maps for aircraft gas turbine performance calculations[C]//Proceedings of International Gas Turbine and Aeroengine Congress and Exhibition. Birmingham,US: ASME,1996: 164.
|
| [14] |
ZACHOS P K,PACHIDIS V,CHARNLEY B,et al. Flowfield investigation of a compressor cascade at high incidence: part 1: pneumatic probe measurements[C]// Proceedings of ASME Turbo Expo: Power for Land,Sea,and Air. Orlando,US: ASME,2009: 59906.
|
| [15] |
ZACHOS P K,PENGUE F,PACHIDIS V,et al. Flowfield investigation of a compressor cascade at high incidence: Part 2 numerical analysis[C]// Proceedings of ASME Turbo Expo: Power for Land,Sea,and Air,Orlando,US: ASME,2009: 59908.
|
| [16] |
ZACHOS PAVLOS K,IOANNA A,VASSILIOS P,et al. A sub-idle compressor characteristic generation method with enhanced physical background[J]. Journal of Engineering for Gas Turbines and Power,2011,133(8): 081702.
|
| [17] |
饶高,苏三买,翟向博. 指数外推法和支持向量机相结合的压气机特性扩展方法[J]. 航空动力学报,2017,32(3): 749-755. RAO Gao,SU Sanmai,ZHAI Xiangbo. Method of compressor characteristic extension combining exponent extrapolation method with support vector machine[J]. Journal of Aerospace Power,2017,32(3): 749-755. (in Chinese
RAO Gao, SU Sanmai, ZHAI Xiangbo. Method of compressor characteristic extension combining exponent extrapolation method with support vector machine[J]. Journal of Aerospace Power, 2017, 32(3): 749-755. (in Chinese)
|
| [18] |
杨欣毅,沈伟,刘海峰,等. 一种应用滑动最小二乘求取压气机特性的方法[J]. 航空动力学报,2009,24(8): 1741-1746. YANG Xinyi,SHEN Wei,LIU Haifeng,et al. Compressor characteristics generation method using moving least square[J]. Journal of Aerospace Power,2009,24(8): 1741-1746. (in Chinese
YANG Xinyi, SHEN Wei, LIU Haifeng, et al. Compressor characteristics generation method using moving least square[J]. Journal of Aerospace Power, 2009, 24(8): 1741-1746. (in Chinese)
|
| [19] |
WALSH P P,FLETCHER P. Gas turbine performance[M]. 2nd ed. Malden,US: Blackwell Science,2004.
|
| [20] |
FERRER-VIDAL L E,PACHIDIS V,TUNSTALL R J. Generating axial compressor maps to zero speed[J]. Proceedings of the Institution of Mechanical Engineers: Part A Journal of Power and Energy,2021,235(5): 956-973.
|
| [21] |
SONG Fu,ZHOU Li,WANG Zhanxue,et al. Integration of high-fidelity model of forward variable area bypass injector into zero-dimensional variable cycle engine model[J]. Chinese Journal of Aeronautics,2021,34(8): 1-15.
|
| [22] |
KENNEDY J,EBERHART R. Particle swarm optimization[C]//Proceedings of IEEE International Conference on Neural Networks. Piscataway,US: IEEE,1995: 1942-1948.
|
| [23] |
GAUDET S R,DONALD GAUTHIER J E. A simple sub-idle component map extrapolation method[C]// Proceedings of ASME Turbo Expo: Power for Land,Sea,and Air,Montreal,Canada: ASME,2007: 27193.
|
| [24] |
欧阳慈. 某型燃气轮机建模与自适应控制研究[D]. 南京: 南京航空航天大学,2018. OUYANG Ci. Research on modeling and adaptive control of a gas turbine[D]. Nanjing: Nanjing University of Aeronautics and Astronautics,2018. (in Chinese
OUYANG Ci. Research on modeling and adaptive control of a gas turbine[D]. Nanjing: Nanjing University of Aeronautics and Astronautics, 2018. (in Chinese)
|
| [25] |
ZACHOS P K. Gas turbine sub-idle performance modelling: altitude relight and windmilling[D]. Cranfield,UK: Cranfield University,2010
|
DownLoad:
