颤振飞行试验的边界预测方法回顾与展望
收稿日期: 2014-12-02
修回日期: 2015-01-30
网络出版日期: 2015-02-10
基金资助
陕西省"青年科技新星"计划 (2014KJXX-36); 航空科学基金(20141330001)
Review and prospect of flutter boundary prediction methods for flight flutter testing
Received date: 2014-12-02
Revised date: 2015-01-30
Online published: 2015-02-10
Supported by
Youth Science and Technology Star Plan of Shanxi Province (2014KJXX-36); Aeronautical Science Foundation of China(20141330001)
颤振飞行试验是新型机种定型必不可少的环节,其目的是要确定颤振边界。由于颤振飞行试验的风险大、耗费高并且周期长,研究者一直在追求安全、准确和高效的颤振边界预测方法。鉴于此,在总结前人研究的基础上,从传统的颤振边界预测方法及其改进和新的颤振边界预测方法两个层面展开,对常用的和近年发展的颤振边界预测方法较为全面而相对简洁的论述,着重介绍了各种颤振边界预测方法的基本原理、适用性及其推广和改进。针对各种方法的原理和特点,将其归纳为构造稳定性参数的方法和基于流固耦合分析模型的方法,并对两类方法进行了对比和总结。最后,对目前颤振边界预测存在的一些技术难点及其发展趋势进行了初步的探讨。
张伟伟 , 钟华寿 , 肖华 , 叶正寅 . 颤振飞行试验的边界预测方法回顾与展望[J]. 航空学报, 2015 , 36(5) : 1367 -1384 . DOI: 10.7527/S1000-6893.2015.0036
Flight flutter testing, whose objective is to identify the flutter boundary, is an indispensible course for new aircraft to finalize. Because of the extremely great risk, high consumption and long period, researchers have been always pursuing a more secure, accurate and efficient flutter boundary prediction method. Based on the summary and analysis of the previous research, from the aspects of conventional flutter boundary prediction methods and new methods for flight flutter testing, this paper makes a more comprehensive and relatively concise introduction of many kinds of flutter prediction methods, and it highlights the basic principles, merits and demerits as well as the development of these methods. According to the fundamental principles and characteristics of various methods, they are divided into two categories, namely, introducing stability parameters methods and considering a coupled fluid-structure system method. Then, the two kinds of methods are compared and summarized. Finally, technical difficulties encountered at present and the development trend in the field of flight flutter testing are preliminary discussed.
[1] Von Schlippe B. The question of spontaneous wing oscillation: determination of critical velocity through flight-oscillation tests[J]. Luftfahrtforschung, 1936, 13(2): 41-45.
[2] Kohoe M. W. A history overview of flight flutter testing, NASA TM-4720[R]. Edwards: NASA Dryden Flight Research Center, 1995.
[3] Kayran A. Flight flutter testing and aeroelastic stability of aircraft[J]. Aircraft Engieering and Aerospace Technology: An International Journal, 2007, 79(5): 494-506.
[4] Dimitriadis G, Cooper J E. Flutter prediction from flight flutter test data[J]. Journal of Aircraft, 2001, 38(2): 355-367.
[5] Lind R. Flight-test evaluation of flutter prediction methods[J]. Journal of Aircraft, 2003, 40(5): 964-970.
[6] Zimmerman N H, Weissenburger J T. Prediction of flutter onset speed based on flight testing at subcritical speeds[J]. Journal of Aircraft, 1964, 1(4): 190-202.
[7] Cooper J E, Emmet P R, Wright J, et al. Envelope function: a tool for analyzing flutter data[J]. Journal of Aircraft, 1993, 30(5): 785-790.
[8] Matsuzaki Y, Ando Y. Estimation of flutter boundary from random responses due to turbulence at subcritical speeds[J]. Journal of Aircraft, 1981, 18(10): 826-868.
[9] Nissim E, Gilyard G B. Method for experimental determination of flutter speed by parameter identification, AIAA-1989-1324[R]. Reston: AIAA, 1989.
[10] Lind R. A presentation on robust flutter margin analysis and a flutterometer, NASA TM-97-206220 [R]. Edwards: NASA Dryden Flight Research Center, 1997.
[11] Zeng Q H, Zhang L M, Zhang C N. Data analysis and software development for flight flutter test[J]. Acta Aeronautica et Astronautica Sinica,1994,12(15): 1482-1485 (in Chinese). 曾庆华, 张令弥, 张春宁. 飞行颤振试验数据处理方法及软件研制[J].航空学报, 1994, 12(15): 1482-1485.
[12] Qu J Z, Sha C A. Application of identification method of modal parameter to flight flutter test[J]. Acta Aeronautica et Astronautica Sinica, 1990,11(11): A618-A622 (in Chinese). 屈见忠, 沙长安.模态参数识别在飞行颤振试验中的应用[J].航空学报, 1990, 11(11): A618-A622.
[13] Vecchio A, Peeters B, Vander Auweraer H. Application of advanced parameter estimators to the analysis of in-flight measured data[C]//Proceedings of the 20th International Modal Analysis Conference. Los Angeles: Society for Experimental Mechanics, 2002: 923-929.
[14] Lee B H K, Ben-Neticha Z. Analysis of flight flutter test data[J]. Canadian Aeronautics and Space Journal, 1992,38(4): 156-163.
[15] Koenig K. Flight vibration analysis-methods, theory and application, AIAA-1983-2752[R]. Reston: AIAA, 1983.
[16] Cooper J E. Parameter estimation methods for flight flutter testing[C]//The 80th Meeting of the AGARD Structures and Materials Panel. Rotterdam: AGARD Advisory Group for Aerospace Research and Development,1995: 121-132.
[17] Shelley S J, Pickrel C R. New concepts for flight flutter parameter estimation[C]//Proceedings of the 15th International Modal Analysis Conference. Orlando: SPIE-International Society for Optical Engineering,1997: 490-496.
[18] Crowther W J, Cooper J E. Flight test flutter prediction using neural networks[J]. Journal of Aerospace Engineering, 2001, 215(1): 37-47.
[19] Chen K F, Jiao Q Y. Modal parameters identification of an aircraft under flutter test flying[J]. Acta Aeronautica et Astronautica Sinica, 2003, 24(6): 526-530 (in Chinese). 陈奎孚, 焦群英. 某型飞机颤振试飞数据的模态参数识别[J]. 航空学报, 2003, 24(6): 526-530.
[20] Marchitti M. Averaging apectral functions fron in flight flutter siganal[J]. Mechanical Systems and Signal Processing, 2006, 20(3): 757-761.
[21] Tang W, Shi Z K, Li H C. Frequency-domain GTLS identification combined with time-frequency filtering for flight flutter modal parameter identification[J]. Chinese Journal of Aeronautics, 2006, 19(1): 44-51.
[22] Lu X D. Flutter flight test parameters identification of large aircraft with low-frequency and closely-spaced modes [J]. Flight Dynamic, 2014, 32(3): 270-272 (in Chinese). 卢晓东.大型飞机颤振试飞低频密集模态参数辨识[J].飞行力学, 2014, 32(3): 270-272.
[23] Verboven P, Cauberghe B, Guillaume P, et al. Modal parameter estimation and monitoring for on-line flight flutter analysis[J]. Mechanical System and Signal Processing, 2004, 18(3): 587-610.
[24] Uhl T, Petko M. Real-time flutter detection from in-flight vibration data[J]. Key Engineering Materials, 2007, 347(679): 679-684.
[25] Ertveldt J, Lataire J, Pintelon R, et al. Flutter speed prediction based on frequency-domain identification of a time-varying system[C]//International Conference in Noise and Vibration Engineering. Leuven: ISMA, 2012: 3013-3024.
[26] Ertveldt J, Lataire J, Pintelon R,et al. Frequency-domain identification of time-varying systems for analysis and prediction of aeroelastic flutter[J]. Mechanical Systems and Signal Processing, 2014, 47(1-2): 225-242.
[27] Lind R, Brenner M, Haley S. Estimation of modal parameters using a wavelet-based approach, AIAA-1997-3836[R]. Reston: AIAA, 1997.
[28] Lind R, Brenner M. Wavelet-processed flight data for robust aeroservoelastic stability margins[J]. Journal of Guidance, Control, and Dynamics, 1998, 21(6): 823-829.
[29] Sahasrabudhe V, Thompson P M, Klyde D H, et al. Flutter detection using wavelet-based time-varying transfer functions, AIAA-2000-4100[R]. Reston: AIAA, 2000.
[30] Staszewski W J, Cooper J E. Wavelet approach to flutter data analysis[J]. Journal of Aircraft, 2002,39(1): 125-132.
[31] Lardies J, Gouttebroze S. Identification of modal parameters using the wavelet transform[J]. International Journal of Mechanical Sciences, 2002, 44( 11): 2263-2283.
[32] Slavie J, Simonovski I, Bolterzar M. Damping identification using a continuous wavelet transform: application to real data[J] . Journal of Sound and Vibration, 2003, 262: 291- 307.
[33] Tang W, Shi Z K. Wavelet denoising of flight flutter testing data for improvement of parameter identification[J]. Chinese Journal of Aeronautics, 2005, 18(1): 72-77.
[34] Zhang B, Shi Z K, Li J J. Flight flutter modal parameters identification with atmospheric turbulence excitation based on wavelet transformation[J]. Chinese Journal of Aeronautics, 2007, 20(5): 394-401.
[35] Tang W, Shi Z K. Wavelet identification of flight flutter modal parameters under sweep excitation[J]. Journal of Vibration and Shock, 2009, 28(2): 172-177.
[36] Dickinson M. CF-18 flight flutter test(FFT) techniques[C]//The 80th Meeting of the AGARD Structures and Materials Panel. Rotterdam: AGARD Advisory Group for Aerospace Research and Development, 1995: 133-141.
[37] Bennett R M. Application of zimmerman flutter-margin criterion to a wind-tunnel model, NASA TM-84545[R]. Hampton: NASA Langly Research Center, 1982.
[38] Kadrnka E E. Multimode instability prediction method. AIAA-1985-0737[R]. Reston: AIAA, 1987.
[39] Price S J, Lee B H K. Evaluation and extension of the flutter margin method for flight flutter prediction[J]. Journal of Aircraft, 1993, 30(3): 395-402.
[40] Lind R. Flutter margins for multimode unstable couplings with associated flutter confidence [J]. Journal of Aircraft, 2009, 46(5): 1563-1568.
[41] Poirel D, Dunn S, Porter J. Flutter-margin method accounting for modal parameter uncertainties[J]. Journal of Aircraft, 2005, 42(5): 1236-1243.
[42] Pitt D M. Flutter margin determination for single degree-of-freedom aeroelastic instabilities[C]//International Forum on Aeroelasticity and Structural Dynamics. Madrid: Associated de Ingenieros Aeronauticos de Espana, 2011:321-332.
[43] Abbasi A A, Cooper J E. Development of the envelope function for flight flutter testing[C]//23rd International Conference on Noise and Vibration Engineering. Leuven: ISMA, 2008: 1183-1196.
[44] Cooper J E, Desforges M J, Wright J R. The online envelope function - a guide to aeroelastic stability[C]//International Forum on Aeroelasticity and Structural Dynamics. Reston: AIAA, 1993: 981-998.
[45] Matsuzaki Y, Ando Y. Flutter and divergence boundary prediction from nonstationary random responses at increasing flow speeds, AIAA-1985-0691[R]. Reston: AIAA, 1985.
[46] Matsuzaki Y, Torii H. Response characteristics of a two-dimensional wing subject to turbulence near the flutter boundary[J]. Journal of Sound and Vibration, 1990,136(2): 187-199.
[47] Torii H, Matsuzaki Y. Subcritical flutter characteristics of a swept-back wing in a turbulent supersonic flow: comparison between analysis and experiment, AIAA-1992-2393[R]. Reston: AIAA, 1992.
[48] Torii H, Matsuzaki Y. Flutter boundary prediction based on nonstationary data measurement[J]. Journal of Aircraft, 1997, 34(3): 427-432.
[49] Torii H, Matsuzaki Y. Flutter margin evaluation for discrete-time systems[J]. Journal of Aircraft, 2011, 38(1): 42-47.
[50] McNamara J J, Friedmann P P. Flutter-boundary identification for time-domain computational aeroelasticity[J]. AIAA Journal, 2007, 45(7): 1546-1555.
[51] Bae J S, Kim J Y, Lee I, et al. Extension of flutter prediction parameter for multi-mode flutter system[J]. Journal of Aircraft, 2005, 42(1): 285-288.
[52] Matsuzaki Y. Flutter boundary prediction of a digitized aeroelastic multi-mode system, AIAA-2008-2316[R]. Reston: AIAA, 2008.
[53] Matsuzaki Y. Flutter boundary prediction of digitized smart multimode systems using steady-state responses, AIAA-2009-2315[R]. Reston: AIAA, 2009.
[54] Cooper J E. Comment on flutter prediction from flight flutter test data[J]. Journal of Aircraft, 2006, 43(3): 862-863.
[55] Lind R, Brenner M. Robust flutter margins of an F/A-18 aircraft from aeroelastic flight data[J]. Journal of Guidance, Control, and Dynamics, 1997, 20(3): 597-604.
[56] Lind R, Brenner M. Robust flutter margin analysis that incorporate flight data, NASA TP-1998-206543[R]. Edwards: Dryden Flight Research Center, 1998..
[57] Lind R, Brenner M. Robust aeroservoelastic stability analysis: flight test application[M]. London: Springer Verlag, 1999: 55-195.
[58] Packard A, Doyle J. The complex structured singularvalue[J]. Automatica, 1993, 29(1): 71-109.
[59] Balas G, Doyle J, Glover K, et al. μ-analysis and synthesis toolbox user’s guide[M]. Natick MA: The MathWorks, 1991, 4: 3-84.
[60] Lind R, Brenner M. Flutterometer: an on-line tool to predict robust flutter margins[J]. Journal of Aircraft, 2000, 37(6): 1105-1112.
[61] Borglund D. The μ-k method for method for robust flutter solution[J]. Journal of Aircraft, 2004, 41(5): 1209-1216.
[62] Borglund D, Ringertz U. Efficient computation of robust futter boundaries using the μ-k method[J]. Journal of Aircraft, 2006, 43(6): 1763-1769.
[63] Wu Z G, Yang C. A new approach for aeroelastic rubost stability analysis[J]. Journal of Aeronautics, 2008, 21(5): 417-422.
[64] Dai Y T, Yang C. Intrusive flutter solutions with stochastic uncertainty[J]. Acta Aeronautica et Astronautica Sinica, 2014, 35(8): 2182-2189 (in Chinese). 戴玉婷, 杨超. 考虑随机型不确定性的浸入式颤振求解方法[J]. 航空学报, 2014, 35(8): 2182-2189.
[65] Yang Z C, Gu Y S, Li B. On the continuity of frequency domain μ analysis and complex perturbationmethod for flutter solution[J]. Journal of Vibration and Shock, 2009, 28(5): 55-58 (in Chinese). 杨智春, 谷迎松, 李斌. 频域颤振μ分析的连续性即复摄动方法研究[J]. 振动与冲击, 2009, 28(5): 55-58.
[66] Gu Y S, Yang Z C, Li B. Flutter prediction based on multiplicative perturbation to dynamic pressure[J]. Acta Aeronautica et Astronautica Sinica, 2009, 30(12): 2311-2315 (in Chinese). 谷迎松, 杨智春, 李斌.采用乘性速压摄动的频域颤振预测方法[J]. 航空学报, 2009, 30(12): 2311-2315.
[67] Yuan H W, Han J L, Huang L L. Model validation and robust flutter analysis of uncertain aeroelastic systems[J]. Journal of Vibration Engineering, 2009, 22(5): 449-455 (in Chinese). 员海玮, 韩景龙, 黄丽丽. 气动弹性系统的模型确认与鲁棒颤振分析[J]. 振动工程学报, 2009, 22(5): 449-455.
[68] Yuan H W. Research on robust flutter analysis and model validation[D]. Nanjing: Nanjing University of Aeronautics and Astronautics, 2008 (in Chinese). 员海玮. 鲁棒颤振分析与模型确认研究[D]. 南京: 南京航空航天大学, 2008.
[69] Lind R. Match-point solution for robust flutter analysis[J]. Journal of Aircraft, 2002, 39(1): 91-99.
[70] Yuan H W, Han J L. Calculation method for robust flutter based on altitude perturbation[J]. Journal of Nanjing University of Aeronautics & Astronautics, 2007, 39(6): 731-735 (in Chinese). 员海玮, 韩景龙. 飞行高度摄动的鲁棒颤振计算方法[J]. 南京航空航天大学学报, 2007, 39(6): 731-735.
[71] Yuan H W, Han J L. Match point solution for robust flutter analysis in constant-mach prediction[J]. Chinese Journal of Aeronautics, 2008, 21(2): 105-114.
[72] Chuang C H, Shin S J, Kim T. Development of an aircraft worst case flutter prediction with mach variation using robust stability analysis[J]. Journal of Mechanical Science and Technology, 2009, 23(8): 2059-2071.
[73] Chuang C H, Shin S J. Validation of a robust flutter prediction by optimization[J]. International Journal of Aeronautical and Space Sciences, 2012, 13(1): 43-57 .
[74] Baldelli D H, Lind R, Brenner M. Data-based robust match-point solution using describing function method, AIAA-2005-1857[R]. Reston: AIAA, 2005.
[75] Baldelli D H, Lind R, Brenner M. Nonlinear aeroelastic/aeroservoelastic modeling by block-oriented identification[J]. Journal of Guidance, Control and Dynamics, 2005, 28(5): 1056-1064.
[76] Yuan H W, Han J L. Robust stability analysis of nonlinear aeroelastic systems[J]. Journal of Vibration Engineering, 2008, 21(4): 329-334 (in Chinese). 员海玮, 韩景龙. 非线性气动弹性系统的鲁棒稳定性分析[J].振动工程学报, 2008, 21(4): 329-334.
[77] Yun H W, Han J L. Robust flutter analysis of a nonlinear aeroelastic system with parameter uncertainties [J]. Aerospace Science and Technology, 2009, 13(2-3): 139-149.
[78] Song J, Kim T, Song S J. Experimental determination of unsteady aerodynamic coefficients and flutter behavior of a rigid wing[J]. Journal of Fluid and Structures, 2012, 29: 50-61.
[79] Kim T. System identification for coupled fluid-structures: aerodynamics is aeroelasticity minus structure[J]. AIAA Journal, 2011, 49(3): 503-512.
[80] Zhang W W, Yu J J, Quan J G, et al. A new flutter prediction method based on a structural response at sub-critical speed[J]. Advanced in Aeronautical Science and Engineering, 2012, 3(4): 390-396 (in Chinese). 张伟伟, 于俊杰, 全景阁, 等. 一种基于亚临界响应的颤振边界预测新方法[J]. 航空工程进展, 2012, 3(4): 390-396.
[81] Cowan T J, Andrew S, Gupta K K. Accelerating computational fluid dynamics based aeroelastic predictions using system identification[J]. Journal of Aircraft, 2001, 38(1): 81-87.
[82] Zhang W W, Ye Z Y. Reduced-order-model-based flutter analysis at high angle of attack[J]. Journal of Aircraft, 2007, 44(6): 2086-2089.
[83] Zhang W W, Ye Z Y. Effect of control surface on airfoil flutter in transonic flow[J]. Acta Astronautica, 2010, 66(7/8): 999-1007.
[84] Afolabi D, Pidaparti R M V, Yang H T Y. Flutter prediction using eigenvector orientation approach[J]. AIAA Journal, 1998, 36(1): 69-74.
[85] Turevskiy A, Feron E, Paduano J. Flutter boundry prediction using physical modes and experimental data[J]. Journal of Guidance, 1998, 22(1): 168-171.
[86] Ueda T, Iio M, Ikeda T. Flutter prediction using continuous wavelet transform[J]. Transactions of the Japan Society for Aeronautical and Space Sciences, 2008, 51(174): 275-281.
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