Optimization of compressor variable stator vane angles based on particle swarm algorithm
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摘要:
为加速多级轴流压气机可调静叶角度优化试验，降低试验成本，提出一种利用数值计算指导试验的方法。将压气机级负荷与设计目标的匹配作为优化方向，基于粒子群算法建立了优化模型，利用少量试验数据作为输入，实现了多级静叶角度同步寻优。利用CFD数据代替试验数据进行了模型验证，优化角度下压气机可调级的负荷匹配明显优于初始角度。两台压气机的性能试验结果表明：优化角度下压气机可调级的单级换算流量和单级压比与设计目标的平均偏差均在±0.5%以内，匹配精度高。此外，对于共同工作线附近的状态点，压气机的绝热效率得到了提升。相比于传统的试验方法，利用粒子群优化数值计算指导5级可调静叶的角度优化试验，需要测试的角度组合数量减少约50%。
Abstract:In order to speed up the optimization test of variable stator vane angle of multistage compressor and reduce the test cost, a method using numerical computation to guide test was proposed. Target on matching of the compressor stage load with the design intent, the model was established based on particle swarm optimization. Using a small amount of test data as input, multistage stator vane angles could be optimized synchronously. Taking CFD data instead of test data, optimized angle combination was proposed using the model herein. The outcomes showed that the load distribution of compressor variable stages at optimized angle was significantly improved than the original one. The performance test result of two compressors showed that the deviations of stage mass flow and stage pressure ratio for variable stages were both within ±0.5% to the design intent, presenting a high accuracy. In addition, the adiabatic efficiency of the compressor was improved at operation points near the working line. Taking the advantage of particle swarm optimization, the tested angle combinations were approximately 50% less required than the conventional methodology.
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图 3 S2不同角度下压气机可调级的归一化单级特性
Figure 3. Normalized stage characteristics of the variable stages of compressor at different S2 angles
图 4 S2角度对压气机可调级换算流量的影响
Figure 4. Influence of S2 angle on mass flow of the variable stages of compressor
图 5 S2角度对压气机可调级压比的影响
Figure 5. Influence of S2 angle on pressure ratio of the variable stages of compressor
图 8 优化角度与初始角度下的单级特性对比
Figure 8. Stage characteristics comparison between optimized angles and original angles
图 9 优化角度与初始角度下的单级特性对比（压气机#1）
Figure 9. Stage characteristics comparison between optimized angles and original angles （compressor #1）
图 10 优化角度与初始角度下的单级特性对比（压气机#2）
Figure 10. Stage characteristics comparison between optimized angles and original angles （compressor #2）
图 11 共同工作线附近状态点的效率提升量
Figure 11. Efficiency improvement at operation points near working line
表 1 优化角度下单级特性与设计目标的平均偏差
Table 1. Average deviation between stage characteristics and design intent at optimized angles
% 压气机序号 换算流量偏差 压比偏差 #1 0.33 0.32 #2 0.49 0.23 
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[1] 张健, 任铭林. 静叶角度调节对压气机性能影响的试验研究[J]. 航空动力学报, 2000, 15(1): 27-30. ZHANG Jian, REN Minglin. Experimental investigation on effect of stator vane angle adjustment on compressor performance[J]. Journal of Aerospace Power, 2000, 15(1): 27-30. (in ChineseZHANG Jian, REN Minglin. Experimental investigation on effect of stator vane angle adjustment on compressor performance[J]. Journal of Aerospace Power, 2000, 15(1): 27-30. (in Chinese) [2] 夏联, 崔健, 顾扬. 可调静叶对压气机低速性能影响的试验研究[J]. 燃气涡轮试验与研究, 2005, 18(1): 31-34. XIA Lian, CUI Jian, GU Yang. An experimental investigation on the effect of variable stator vane angle on compressor performance at low speed[J]. Gas Turbine Experiment and Research, 2005, 18(1): 31-34. (in ChineseXIA Lian, CUI Jian, GU Yang. An experimental investigation on the effect of variable stator vane angle on compressor performance at low speed[J]. Gas Turbine Experiment and Research, 2005, 18(1): 31-34. (in Chinese) [3] 宋文艳, 李新, 范非达. 多级压气机可调静叶转角的多目标优化研究[J]. 推进技术, 1997, 18(4): 26-30. SONG Wenyan, LI Xin, FAN Feida. Investigation on multi-objective optimizing angle of variable stator of axial-flow compressor[J]. Journal of Propulsion Technology, 1997, 18(4): 26-30. (in ChineseSONG Wenyan, LI Xin, FAN Feida. Investigation on multi-objective optimizing angle of variable stator of axial-flow compressor[J]. Journal of Propulsion Technology, 1997, 18(4): 26-30. (in Chinese) [4] SUN J, ELDER R L. Numerical optimization of a stator vane setting in multistage axial-flow compressors[J]. Proceedings of the Institution of Mechanical Engineers, Part A: Journal of Power and Energy, 1998, 212(4): 247-259. doi: 10.1243/0957650981536772 [5] GALLAR L, ARIAS M, PACHIDIS V, et al. Compressor variable geometry schedule optimisation using genetic algorithms[J]. Proceedings of the ASME Turbo Expo, 2009, 4: 425-434. [6] GALLAR L, ARIAS M, PACHIDIS V, et al. Stochastic axial compressor variable geometry schedule optimisation[J]. Aerospace Science and Technology, 2011, 15(5): 366-374. doi: 10.1016/j.ast.2010.08.010 [7] 吴虎, 孙娜. 多级轴流压气机变几何扩稳优化方法研究[J]. 航空动力学报, 2009, 24(11): 2558-2563. WU Hu, SUN Na. Method of optimization of a stator vane setting in multistage axial-flow compressors[J]. Journal of Aerospace Power, 2009, 24(11): 2558-2563. (in ChineseWU Hu, SUN Na. Method of optimization of a stator vane setting in multistage axial-flow compressors[J]. Journal of Aerospace Power, 2009, 24(11): 2558-2563. (in Chinese) [8] 吴虎, 毛凯, 孙娜. 多级轴流压气机变几何扩稳优化与性能约束分析[J]. 航空发动机, 2012, 38(6): 11-15. WU Hu, MAO Kai, SUN Na. Analysis of variable geometry aerodynamic stability optimization and performance constraints for multistage axial-flow compressor[J]. Aeroengine, 2012, 38(6): 11-15. (in ChineseWU Hu, MAO Kai, SUN Na. Analysis of variable geometry aerodynamic stability optimization and performance constraints for multistage axial-flow compressor[J]. Aeroengine, 2012, 38(6): 11-15. (in Chinese) [9] 史磊, 刘波, 张鹏, 等. 商用发动机10级高压压气机一维特性优化设计[J]. 航空动力学报, 2013, 28(7): 1564-1569. SHI Lei, LIU Bo, ZHANG Peng, et al. One-dimensional characteristic optimization design for ten-stage high pressure compressor in commercial engine[J]. Journal of Aerospace Power, 2013, 28(7): 1564-1569. (in ChineseSHI Lei, LIU Bo, ZHANG Peng, et al. One-dimensional characteristic optimization design for ten-stage high pressure compressor in commercial engine[J]. Journal of Aerospace Power, 2013, 28(7): 1564-1569. (in Chinese) [10] REITENBACH S, SCHNOS M, BECKER R G, et al. Optimization of compressor variable geometry setting using multi-fidelity simulation[R]. ASME Paper GT 2015-42832, 2015. [11] 廖吉香, 姜斌, 吕从鹏, 等. 多级轴流压气机多排可转导/静叶联合调节规律研究[J]. 推进技术, 2017, 38(2): 334-340. LIAO Jixiang, JIANG Bin, LV Congpeng, et al. Numerical optimization of combined adjustment of multi-row variable inlet guide vane and stators in a multistage axial-flow compressor[J]. Journal of Propulsion Technology, 2017, 38(2): 334-340. (in ChineseLIAO Jixiang, JIANG Bin, LV Congpeng, et al. Numerical optimization of combined adjustment of multi-row variable inlet guide vane and stators in a multistage axial-flow compressor[J]. Journal of Propulsion Technology, 2017, 38(2): 334-340. (in Chinese) [12] 张夏雯, 琚亚平, 张楚华. 多级轴流压气机性能预测及导静叶调节优化[J]. 工程热物理学报, 2020, 41(6): 1418-1424. ZHANG Xiawen, JU Yaping, ZHANG Chuhua. Performance prediction and IGV-stator adjustment optimization of a multi-stage axial-flow compressor[J]. Journal of Engineering Thermophysics, 2020, 41(6): 1418-1424. (in ChineseZHANG Xiawen, JU Yaping, ZHANG Chuhua. Performance prediction and IGV-stator adjustment optimization of a multi-stage axial-flow compressor[J]. Journal of Engineering Thermophysics, 2020, 41(6): 1418-1424. (in Chinese) [13] 孙鹏, 张君鑫, 张善科, 等. 船用燃气轮机压气机多级可调静叶优化匹配方法研究[J]. 热能动力工程, 2021, 36(5): 40-48. SUN Peng, ZHANG Junxin, ZHANG Shanke, et al. Research on optimization and matching method of multi-stage variable stator vanes for marine gas turbine compressor[J]. Journal of Engineering for Thermal Energy and Power, 2021, 36(5): 40-48. (in ChineseSUN Peng, ZHANG Junxin, ZHANG Shanke, et al. Research on optimization and matching method of multi-stage variable stator vanes for marine gas turbine compressor[J]. Journal of Engineering for Thermal Energy and Power, 2021, 36(5): 40-48. (in Chinese) [14] GARBEROGLIO J E, SONG J O, BOUDREAUX W L. Optimization of compressor vane and bleed settings[R]. ASME Paper 82-GT-81, 1982. [15] 王永明. 多级轴流压气机静叶转角优化计算[J]. 航空动力学报, 1992, 7(1): 77-80, 101. WANG Yongming. Optimization of multistage axial-flow compressor vane setting[J]. Journal of Aerospace Power, 1992, 7(1): 77-80, 101. (in ChineseWANG Yongming. Optimization of multistage axial-flow compressor vane setting[J]. Journal of Aerospace Power, 1992, 7(1): 77-80, 101. (in Chinese) [16] 傅阳光. 粒子群优化算法的改进及其在航迹规划中的应用研究[D]. 武汉: 华中科技大学, 2011. FU Yangguang. Improvement of particle swarm optimization algorithm and its application in route planning[D]. Wuhan: Huazhong University of Science and Technology, 2011. (in ChineseFU Yangguang. Improvement of particle swarm optimization algorithm and its application in route planning[D]. Wuhan: Huazhong University of Science and Technology, 2011. (in Chinese) [17] 孙滢. 若干最优化问题的粒子群算法及应用研究[D]. 合肥: 合肥工业大学, 2020. SUN Ying. Research on particle swarm optimization for some optimization problems and its application[D]. Hefei: Hefei University of Technology, 2020. (in ChineseSUN Ying. Research on particle swarm optimization for some optimization problems and its application[D]. Hefei: Hefei University of Technology, 2020. (in Chinese) [18] 王新峰, 邱静, 刘冠军. 基于离散粒子群优化算法的直升机减速器齿轮故障特征选择[J]. 航空动力学报, 2005, 20(6): 969-972. WANG Xinfeng, QIU Jing, LIU Guanjun. Discrete particle swarm optimization algorithm for gearbox fault symptom selection[J]. Journal of Aerospace Power, 2005, 20(6): 969-972. (in ChineseWANG Xinfeng, QIU Jing, LIU Guanjun. Discrete particle swarm optimization algorithm for gearbox fault symptom selection[J]. Journal of Aerospace Power, 2005, 20(6): 969-972. (in Chinese) [19] 钱海鹰, 杨培源, 徐松林. 基于粒子群算法的发动机部件模型求解[J]. 推进技术, 2012, 33(6): 974-980. QIAN Haiying, YANG Peiyuan, XU Songlin. Application of particle swarm optimization in obtaining solution of aeroengine component-level model[J]. Journal of Propulsion Technology, 2012, 33(6): 974-980. (in ChineseQIAN Haiying, YANG Peiyuan, XU Songlin. Application of particle swarm optimization in obtaining solution of aeroengine component-level model[J]. Journal of Propulsion Technology, 2012, 33(6): 974-980. (in Chinese) [20] 宋召运, 刘波, 程昊, 等. 基于改进粒子群算法的串列叶型优化设计[J]. 推进技术, 2016, 37(8): 1469-1476. SONG Zhaoyun, LIU Bo, CHENG Hao, et al. Optimization of tandem blade based on modified particle swarm algorithm[J]. Journal of Propulsion Technology, 2016, 37(8): 1469-1476. (in ChineseSONG Zhaoyun, LIU Bo, CHENG Hao, et al. Optimization of tandem blade based on modified particle swarm algorithm[J]. Journal of Propulsion Technology, 2016, 37(8): 1469-1476. (in Chinese) [21] 王昭, 田小涛, 黄萌, 等. 基于PSO-BP神经网络的固冲发动机推力估计器设计[J]. 航空动力学报, 2022, 37(7): 1487-1494. WANG Zhao, TIAN Xiaotao, HUANG Meng, et al. Design of thrust estimator in the solid rocket ramjet based on PSO-BP neural network[J]. Journal of Aerospace Power, 2022, 37(7): 1487-1494. (in ChineseWANG Zhao, TIAN Xiaotao, HUANG Meng, et al. Design of thrust estimator in the solid rocket ramjet based on PSO-BP neural network[J]. Journal of Aerospace Power, 2022, 37(7): 1487-1494. (in Chinese) [22] CHATTERJEE A, SIARRY P. Nonlinear inertia weight variation for dynamic adaptation in particle swarm optimization[J]. Computers & Operations Research, 2006, 33(3): 859-871. -
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