在压气机三维动叶片结构参数中，叶型的前缘角、后缘角、前后缘形状、弦长、厚度、不同叶高位置这6个典型参数同时受加工误差影响，对压气机性能影响较大。为找出叶片加工误差对压气机性能的影响规律，对某跨声速压气机转子叶片的加工误差进行了研究，针对加工误差引起的上述6个典型结构参数变化，归纳出3个加工水平，并采用正交实验法设计出27个样本，通过数值计算对所有样本的性能进行对比分析。结果表明这6个典型结构参数的加工误差综合作用对压气机的总压比、效率、流量影响较大，增加的最大量分别为2.02%、1.47%、1.87%，减小的最大量分别为-0.87%、-1.42%、-0.88%，极差分析表明影响效率的主要参数为前缘角误差、厚度误差，影响总压比的主要参数为前后缘形状、厚度误差、不同叶高位置，影响流量的主要参数为前缘角误差、前后缘形状，回归线性分析证实压气机效率、流量的变化与上述典型参数的加工误差综合作用成线性关系。
Among three-dimensional compressor blade structure parameters, the leading edge angle, trailing edge angle, front and rear edge shape, chord length, thickness, and different span position of blade profile are affected by machining errors at the same time, which have great influence on compressor performance. In order to find out the influence of blade processing errors on compressor performance, the processing errors of a transonic compressor blade are studied. The variation of six typical structural parameters mentioned above caused by machining errors is summarized into three processing levels, and 27 samples are designed by an orthogonal experiment method. The performance of all samples is compared and analyzed by numerical calculation. The results show that the combined effect of processing errors of these six typical structural parameters has a great influence on the total pressure ratio, efficiency and flow rate of compressor. The maximum increases are 2.02%, 1.47%, 1.87%, and the maximum decreases are -0.87%, -1.42%, -0.88%. Range analysis shows that the main parameters affecting efficiency are leading edge angle error and thickness error. The main parameters affecting total pressure ratio are leading edge shape, thickness error, and different span positions. The main parameters affecting flow rate are leading edge angle error and leading edge shape. Linear regression analysis confirms that the variation of compressor efficiency and flow rate are linearly related to the processing errors of the typical parameters mentioned above.
[1] 陈亚莉, 李美荣, 宋成. 压气机叶片型面精密数控铣加工技术应用研究[J]. 航空发动机, 2016, 42(4):93-97. CHEN Y L, LI M R, SONG C. Investigation on precision nc milling technology of compressor blade surface[J]. Aeroengine, 2016, 42(4):93-97(in Chinese).
[2] ROELKE R J, HAAS J E. The effect of rotor blade thickness and surface finish on the performance of a small axial flow turbine[J]. Journal of Engineering for Power, 1983, 105(2):377-382.
[3] SUDER K L, CHIMA R V, STRAZISAR A J, et al. The effect of adding roughness and thickness to a transonic axial compressor rotor[J]. Journal of Turbomachinery, 1995, 117(4):491-505.
[4] ROBERTS W B, ALBERT A, GEORGE K, et al. The effect of variable chord length on transonic axial rotor performance[J]. Journal of Turbomachinery, 2002, 124(3):351-357.
[5] GOODHAND M N, MILLER R J. Compressor leading edge spikes:A new performance criterion[J]. Journal of Turbomachinery, 2010, 133(2):021006.
[6] GOODHAND M N, MILLER R J. The impact of real geometries on three-dimensional separations in compressors[J]. Journal of Turbomachinery, 2011, 134(2):021007.
[7] DARIA K, OLEG B, GRIGORII P. Effect of manufacturing tolerances on the turbine blades:ASME GTINDIA2014-8253[R]. 2014.
[8] GARZON V E, DARMOFAL D L. Impact of geometric variability on axial compressor performance[J]. Journal of Turbomachinery, 2003,125(4):692-703.
[9] SCHNELL R, LENGYEL-KAMPMANN T, NICKE E. On the impact of geometric variability on fan aerodynamic performance, unsteady blade row interaction, and its mechanical characteristics[J]. Journal of Turbomachinery, 2014, 136(9):091005.
[10] JAN K, IVAN V, TOAL D J, et al. Robust turbine blade optimization in the face of real geometric variations[J]. Journal of Propulsion and Power, 2018, 34(6):1479-1493.
[11] GOODHAND M N, MILLER R J, LUNG H W. The sensitivity of 2D compressor incidence range to in-service geometric variation:ASME GT2012-68633[R]. 2012.
[12] 高丽敏, 蔡宇桐, 曾瑞慧,等. 叶片加工误差对压气机叶栅气动性能的影响[J]. 推进技术, 2017, 38(3):525-531. GAO L M, CAI Y T, ZENG R H, et al. Effects of blade machining error on compressor cascade aerodynamic performance[J]. Journal of Propulsion Technology, 2017, 38(3):525-531(in Chinese).
[13] 高丽敏, 蔡宇桐, 郝燕平, 等. 加工误差对压气机叶片气动性能影响试验研究[J]. 推进技术, 2017,38(8):1761-1766. GAO L M, CAI Y T, HAO Y P, et al. Experimental investigation on aerodynamic performance of compressor blade considering manufacturing error[J]. Journal of Propulsion Technology, 2017, 38(8):1761-1766(in Chinese).
[14] 张伟昊, 邹正平, 李维, 等. 叶型偏差对涡轮性能影响的非定常数值模拟研究[J]. 航空学报, 2010, 31(11):2130-2138. ZHANG W H, ZOU Z P, LI W, et al. Unsteady numerical simulation investigation of effect of blade profile deviation on turbine performance[J]. Acta Aeronautica et Astronautica Sinica, 2010, 31(11):2130-2138(in Chinese).
[15] 郑似玉, 滕金芳, 羌晓青. 叶片加工超差对高压压气机性能影响和敏感性分析[J]. 机械工程学报, 2018, 54(2):216-224. ZHENG S Y, TENG J F, QIANG X Q. Sensitivity analysis of manufacturing variability on high-pressure compressor performance[J]. Journal of Mechanical Engineering, 2018, 54(2):216-224(in Chinese).
[16] 颜勇, 祝培源, 宋立明, 等. 基于非平稳高斯过程的叶栅加工误差不确定性量化[J]. 推进技术, 2017, 38(8):1767-1775. YAN Y, ZHU P Y, SONG L M, et al. Uncertainty quantification of cascade manufacturing error based non-stationary gaussian process[J]. Journal of Propulsion Technology, 2017, 38(8):1767-1775(in Chinese).
[17] 罗佳奇, 朱亚路, 刘锋. 基于伴随方法的叶片加工偏差气动灵敏度分析[J]. 工程热物理学报, 2017, 38(3):498-503. LUO J Q, ZHU Y L, LIU F. Aerodynamic sensitivity analysis for manufacturing variations of a turbine blade by an adjoint method[J]. Journal of Engineering Thermophysics, 2017, 38(3):498-503(in Chinese).
[18] FATHI A, ALIZADEH M. Effects of blade manufacturing deviations on turbine performance:ASME GTINDIA2012-9641[R]. 2012.
[19] GIEBMANNS A, BACKHAUS J, FREY C, et al. Compressor leading edge sensitivities and analysis with an adjoint flow solver:ASME GT2013-94427[R]. 2013.
[20] XIONG J T, LIU F, YANG J, et al. Statistical evaluation of the performance impact of manufacturing variations for steam turbines:ASME GT2016-56553[R]. 2016.
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