The impact detection and identification of foreign objects on aero-engine fans are essential to the flight safety of aircraft. To simulate the impact process of foreign objects on the real engine fan blade, an impact test platform was constructed, and the rule and recognition method of impact on fan blades were studied. Aiming at the problems of high difficulty and low accuracy in identifying the impact of foreign objects on the fan by the airborne parameters and added vibration parameters, we conducted an impact detection experiment of the foreign objects based on the vibration measurement of the non-contact fan blade tip, subsequently proposing an automatic threshold detection system of the foreign object impact on the fan based on the maximum likelihood estimation of the vibration displacement variance. The threshold values of vibration displacement variance identification of the rotor blade tip impacted by foreign objects at different speeds were obtained. The vibration displacement data of the impact of the projectile with a diameter of 16 mm and mass of 2.9 g on the fan blade at the speed of 3 000 r/min was analyzed, with the reliability of the identification result verified by the high-speed camera system. The result shows that the method based on the analysis of non-contact tip vibration displacement variance can accurately identify the impact event, impact location and the number of impact blades.
[1] 杨杰. 风扇叶片鸟撞击响应及受损风扇气动性能分析方法研究[D]. 南京:南京航空航天大学, 2014:1-20. YANG J. Research on response of fan blade subjected to bird strike and aerodynamic performance of damaged fan[D]. Nanjing:Nanjing University of Aeronautics and Astronautics, 2014:1-20(in Chinese).
[2] 陈贺贺. 飞机风挡鸟撞数值模拟研究[D]. 太原:中北大学, 2018:1-15. CHEN H H. Study on numerical simulation of aircraft windshield under bird impact[D]. Taiyuan:North University of China, 2018:1-15(in Chinese).
[3] 尚文. 燃气轮机叶片状态监测技术及故障诊断研究[D]. 北京:北京化工大学, 2014:1-10. SHANG W. Study on the condition monitoring and fault diagnosis of the gas turbine blade[D]. Beijing:Beijing University of Chemical Technology, 2014:1-10(in Chinese).
[4] 张帅, 雷晓波, 张霞妹, 等. 基于统计特征的航空发动机风扇外物撞击检测[J]. 推进技术, 2020, 41(10):2325-2331. ZHANG S, LEI X B, ZHANG X M, et al. Foreign object impact detection of aero-engine fan based on statistical characteristics[J]. Journal of Propulsion Technology, 2020, 41(10):2325-2331(in Chinese).
[5] 张波. 发动机故障引起的民用航空飞行事故分析[D]. 广汉:中国民航飞行学院, 2002:1-25. ZHANG B. Analysis of civil aviation flight accidents caused by engine failure[D]. Guanghan:China Civil Aviation Flight Institute, 2002:1-25(in Chinese).
[6] PETER R. Development of a blade tip timing based engine health monitoring system[D]. Manchester:The University of Manchester, 2010:1-46.
[7] TURSO J A, LITT J S. A foreign object damage event detector data fusion system for turbofan engines[J]. Journal of Aerospace Computing, Information, and Communication, 2005, 2(7):291-308.
[8] FULTON G. Design and qualification of foreign object damage resistant turbofan blades[C]//Proceedings of the 11st AIAA/SAE:Propulsion Conference. Reston:AIAA, 1975:1313.
[9] HEGNER H R. Engine condition monitor system to detect foreign object damage and crack development[C]//Instrumentation for Airbreathing Propulsion. New York:AIAA, 1974:531-547.
[10] HEIMES F, SHEPHARD D, WRIGHT B, et al. Recent progress with the engine health diagnostics using radar system[C]//42nd AIAA/ASME/SAE/ASEE Joint Propulsion Conference & Exhibit. Reston:AIAA, 2006.
[11] SHEPHARD D, WRIGHT B, RICHARDS G. Engine health diagnostics using radar[EB/OL]. Chelmsford:BAE Systems Advanced Technology Centre, 2005.
[12] CARDWELL D N, CHANA K S, GILBOY M T. The development and testing of a gas turbine engine foreign object damage (FOD) detection system[C]//Proceedings of ASME Turbo Expo 2010:Power for Land, Sea, and Air. New York:ASME, 2010:331-342.
[13] 尹冬梅, 钱林方, 栗保明, 等. 外物形状对发动机叶片中残余应力场的影响分析[J]. 机械强度, 2012, 34(3):355-360. YIN D M, QIAN L F, LI B M, et al. Analysis for effects of foreign object shape on the residual stress field of engine blade[J]. Journal of Mechanical Strength, 2012, 34(3):355-360(in Chinese).
[14] 刘超. 叶片外物损伤模拟及其疲劳强度预测技术研究[D]. 南京:南京航空航天大学, 2012:10-34. LIU C. Research on prediction of fatigue strength and simulation for foreign object damage of blade[D]. Nanjing:Nanjing University of Aeronautics and Astronautics, 2012:10-34(in Chinese).
[15] 潘辉. 叶片外物损伤的特征分析及模拟试验研究[D]. 南京:南京航空航天大学, 2012:11-16. PAN H. Research on damage characteristics and simulation test of foreign object damage of blade[D]. Nanjing:Nanjing University of Aeronautics and Astronautics, 2012:11-16(in Chinese).
[16] 季玉辉. 基于Johnson-Cook模型的硬物损伤数值模拟研究[D]. 南京:南京航空航天大学, 2009:1-24. JI Y H. Numerical simulation of hard-body foreign object damage based on Johnson-Cook model[D]. Nanjing:Nanjing University of Aeronautics and Astronautics, 2009:1-24(in Chinese).
[17] 关玉璞, 陈伟, 高德平. 航空发动机叶片外物损伤研究现状[J]. 航空学报, 2007, 28(4):851-857. GUAN Y P, CHEN W, GAO D P. Present status of investigation of foreign object damage to blade in aeroengine[J]. Acta Aeronautica et Astronautica Sinica, 2007, 28(4):851-857(in Chinese).
[18] GUAN Y P, ZHAO Z H, CHEN W, et al. Foreign object damage to fan rotor blades of aeroengine Part I:Experimental study of bird impact[J]. Chinese Journal of Aeronautics, 2007, 20(5):408-414.
[19] GUAN Y P, ZHAO Z H, CHEN W, et al. Foreign object damage to fan rotor blades of aeroengine Part II:Numerical simulation of bird impact[J]. Chinese Journal of Aeronautics, 2008, 21(4):328-334.
[20] 张帅, 雷晓波, 张霞妹, 等. 航空发动机风扇叶片外物撞击识别方法研究[J]. 机械科学与技术, 2020, 39(5):810-814. ZHANG S, LEI X B, ZHANG X M, et al. Research on identification method of foreign object impact of aero-engine fan blade[J]. Mechanical Science and Technology for Aerospace Engineering, 2020, 39(5):810-814(in Chinese).
[21] YE D C, DUAN F J, JIANG J J, et al. Identification of vibration events in rotating blades using a fiber optical tip timing sensor[J]. Sensors, 2019, 19(7):1482.
[22] KHARYTON V, BLADH R. Using tip timing and strain gauge data for the estimation of consumed life in a compressor blisk subjected to stall-induced loading[C]//Proceedings of the ASME Turbo Expo 2014:Turbine Technical Conference and Exposition. New York:ASME, 2014:V07BT33A028.
[23] VERCOUTTER A, LARDIES J, BERTHILLIER M, et al. Improvement of compressor blade vibrations spectral analysis from tip timing data:Aliasing reduction[C]//Proceedings of the ASME Turbo Expo 2013:Turbine Technical Conference and Exposition. New York:ASME, 2013:V07AT26A006.
[24] ZHANG J L, DUAN F J, NIU G Y, et al. A blade tip timing method based on a microwave sensor[J]. Sensors, 2017, 17(5):1097.
[25] 刘志博. 基于叶尖定时的叶片振动参数辨识及耦合振动研究[D]. 北京:华北电力大学, 2017:1-46. LIU Z B. Identification of blade vibration parameters based on blade tip timing and study on coupled vibration[D]. Beijing:North China Electric Power University, 2017:1-46(in Chinese).
[26] 刘美茹, 朱靖, 滕光蓉, 等. 非接触旋转叶片振动测量系统在转子叶片裂纹故障试验中的应用[J]. 燃气涡轮试验与研究, 2015, 28(2):45-48, 52. LIU M R, ZHU J, TENG G R, et al. Non-contact rotating blade vibration measurement system in rotor blade crack fault test[J]. Gas Turbine Experiment and Research, 2015, 28(2):45-48, 52(in Chinese).
[27] 欧阳涛. 基于叶尖定时的旋转叶片振动检测及参数辨识技术[D]. 天津:天津大学, 2011:10-55. OUYANG T. Rotating blade vibration detection and parameters identification technique using blade tip-timing[D]. Tianjin:Tianjin University, 2011:10-55(in Chinese).
[28] 金良琼. 两参数Weibull分布的参数估计[D]. 昆明:云南大学, 2010:1-60. JIN L Q. Two parameter estimation for Weibull distribution[D]. Kunming:Yunnan University, 2010:1-60(in Chinese).
[29] OZAY C, CELIKTAS M S. Statistical analysis of wind speed using two-parameter Weibull distribution in Alaçatı region[J]. Energy Conversion and Management, 2016, 121:49-54.
[30] 温艳清, 刘宝亮. Weibull分布在完全数据条件下的参数估计[J]. 山西大同大学学报(自然科学版), 2009, 25(4):17-19. WEN Y Q, LIU B L. Complete data parameters estimation under Weibull distribution[J]. Journal of Shanxi Datong University (Natural Science Edition), 2009, 25(4):17-19(in Chinese).
[31] 曾国桓. 两参数威布尔分布下定时截尾试验的参数评估方法研究[D]. 成都:电子科技大学, 2018:1-60. ZENG G H. Methods of parameter estimation of two-parameter weibull distribution for type-I censoring test[D]. Chengdu:University of Electronic Science and Technology of China, 2018:1-60(in Chinese).
[32] THOMAS D R, WILSON W M. Linear order statistic estimation for the two-parameter Weibull and extreme-value distributions from type II progressively censored samples[J]. Technometrics, 1972, 14(3):679-691.
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