旋转叶片固有频率识别：基于函数波束形成的叶尖定时信号频谱混叠抑制方法

doi:10.3901/JME.2025.24.028

机械工程学报 ›› 2025, Vol. 61 ›› Issue (24): 28-37.doi: 10.3901/JME.2025.24.028

• 仪器科学与技术 • 上一篇

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旋转叶片固有频率识别：基于函数波束形成的叶尖定时信号频谱混叠抑制方法

张晨宇¹, 肖友洪¹, 肖志成², 余亮^3,4

1. 哈尔滨工程大学动力与能源工程学院哈尔滨 150001;
2. 上海交通大学机械与动力工程学院上海 200240;
3. 西北工业大学民航学院西安 710072;
4. 大型客机集成技术与模拟飞行全国重点实验室上海 200126

收稿日期:2025-03-12 修回日期:2025-08-30 发布日期:2026-01-26
作者简介:张晨宇，男，1998年出生，博士研究生。主要研究方向为叶尖定时信号处理，旋转叶片裂纹预警，声学(阵列)信号处理。E-mail：cyzhang@hrbeu.edu.cn
肖友洪(通信作者)，男，1978年出生，博士，教授，博士研究生导师。主要研究方向为动力装置振动噪声控制，噪声源识别技术以及柴油机排放净化消声一体化控制技术。E-mail：xiaoyouhong@hrbeu.edu.cn
余亮，男，1984年出生，博士，教授，博士研究生导师。主要研究方向为航空机械装备振动和声学，机械装备故障诊断：多物理场测量、数字孪生，人工智能和信号处理。E-mail：liang.yu@nwpu.edu.cn
基金资助:
国家自然科学基金资助项目(12402405，12474464)。

Natural Frequency Identification of Rotating Blades: A Functional Beamforming-based Method for Spectral Aliasing Suppression in Blade Tip Timing Signals

ZHANG Chenyu¹, XIAO Youhong¹, XIAO Zhicheng², YU Liang^3,4

1. College of Power and Energy Engineering, Harbin Engineering University, Harbin 150001;
2. School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240;
3. School of Civil Aviation, Northwestern Polytechnical University, Xi'an 710072;
4. State Key Laboratory of Airliner Integration Technology and Flight Simulation, Shanghai 200126

Received:2025-03-12 Revised:2025-08-30 Published:2026-01-26

摘要/Abstract

摘要： 提出一种函数波束形成方法，用于通过欠采样的叶尖定时信号识别旋转叶片的固有频率。相比于经典的子空间类方法，函数波束形成不需要对信号中的频率个数进行预估，在实际场景下更具应用价值。从常规波束形成的角度出发，推导频率的点传播函数，得到频谱中的频率分量对于波束形成输出的贡献。进一步地，结合频率的点传播函数特性，在互相关常规波束形成的互相关矩阵和输出中引入幂次概念，对频谱中的混叠成分进行抑制，构建函数波束形成的输出量。通过数值仿真和旋转叶盘试验验证所提出的函数波束形成方法的有效性和优越性。结果表明，所提出的函数波束形成方法可以有效抑制频谱混叠，并识别得到目标频率。在信噪比为5 dB时，在给出的数值算例中，所提出的方法可达到100%的识别成功率。在旋转叶盘试验中，对于叶片的两阶固有频率识别的绝对误差不超过1 Hz。

关键词: 叶尖定时, 频谱混叠, 固有频率识别, 函数波束形成, 子空间方法

Abstract: A functional beamforming(FB) method is proposed for identifying the natural frequencies of rotating blades from under-sampled blade tip timing(BTT) signals. Compared with the conventional subspace method, the proposed FB method eliminates the need for pre-estimating the number of frequencies, which makes it more valuable for application in practical scenarios. From the perspective of conventional beamforming(CB), the point spread function(PSF) of frequency in the spectrum is derived, and the contribution of the frequency components in the spectrum to the CB output is obtained. Further, combining the properties of the PSF of frequency, the concept of exponent is introduced into the cross-correlation matrix and output of the CB, the aliasing components in the spectrum are suppressed, and the output of the FB is constructed. The effectiveness and superiority of the proposed FB method are verified by numerical simulation and rotating blade disc experiments. The results show that the proposed FB method can effectively suppress spectral aliasing and identify the target frequency. At a signal-to-noise ratio of 5 dB, the proposed method can achieve a 100% identification success rate in the given numerical examples; in the rotating blade disc experiment, the absolute errors for identifying two-order natural frequencies of the blade do not exceed 1 Hz.

Key words: blade tip timing, spectrum aliasing, natural frequency identification, functional beamforming, subspace method

中图分类号:

TH113

张晨宇, 肖友洪, 肖志成, 余亮. 旋转叶片固有频率识别：基于函数波束形成的叶尖定时信号频谱混叠抑制方法[J]. 机械工程学报, 2025, 61(24): 28-37.

ZHANG Chenyu, XIAO Youhong, XIAO Zhicheng, YU Liang. Natural Frequency Identification of Rotating Blades: A Functional Beamforming-based Method for Spectral Aliasing Suppression in Blade Tip Timing Signals[J]. Journal of Mechanical Engineering, 2025, 61(24): 28-37.

参考文献

[1] 周凯,乔百杰,刘美茹,等. 基于参考键相动态追踪的无转速叶尖定时测量方法[J]. 推进技术,2024,45(8):231-240. ZHOU Kai,QIAO Baijie,LIU Meiru,et al. Blade tip timing measurement method without once-per-revolution sensor based on dynamic tracking of reference key phase[J]. Journal of Propulsion Technology,2024,45(8):231-240.
[2] 李宏坤,魏代同,陈玉刚,等. 数字孪生驱动的旋转叶盘振动状态全景感知方法[J]. 机械工程学报,2023,59(21):270-282. LI Hongkun,WEI Daitong,CHEN Yugang,et al. A full-field sensing method for vibration state of rotating bladed disks driven by digital twin[J]. Journal of Mechanical Engineering,2023,59(21):270-282.
[3] 张玉贵,段发阶,方志强,等. 基于叶尖定时的非接触式旋转叶片异步振动分析[J]. 机械工程学报,2008,44(7):147-150. ZHANG Yugui,DUAN Fajie,FANG Zhiqiang,et al. Analysis of non-contact asynchronous vibration of rotating blades based on tip-timing[J]. Journal of Mechanical Engineering,2008,44(7):147-150.
[4] CHEN Z,SHENG H,XIA Y,et al. A comprehensive review on blade tip timing-based health monitoring:Status and future[J]. Mechanical Systems and Signal Processing,2021,149:107330.
[5] 刘美茹,郜伟强,范毅,等. 叶尖定时技术在转子叶片故障排除中的应用[J]. 航空动力学报,2022,37(12):2818-2829. LIU Meiru,GAO Weiqiang,FAN Yi,et al. Application of blade tip timing technology in rotor blade fault elimination[J]. Journal of Aerospace Power,2022,37(12):2818-2829.
[6] HE C,LI H,ZHAO X. Weak characteristic determination for blade crack of centrifugal compressors based on underdetermined blind source separation[J]. Measurement,2018,128:545-557.
[7] MOON T C,KIM H Y,HWANG W. Natural-frequency reduction model for matrix-dominated fatigue damage of composite laminates[J]. Composite Structures,2003,62(1):19-26.
[8] XU J,QIAO B,LIU M,et al. Crack propagation monitoring of rotor blades using synchroextracting transform[J]. Journal of Sound and Vibration,2021,509:116253.
[9] MAITI S K,WATHARE S M. Fatigue crack growth measurement based on changes in transverse natural frequency[J]. International Journal of Fracture,2006,141(1):339-344.
[10] XU J,QIAO B,LIU M,et al. Blade tip timing for monitoring crack propagation of rotor blades using Block-AOLS[J]. Mechanical Systems and Signal Processing,2022,181:109498.
[11] HEATH S,IMREGUN M. An improved single-parameter tip-timing method for turbomachinery blade vibration measurements using optical laser probes[J]. International Journal of Mechanical Sciences,1996,38(10):1047-1058.
[12] JOUNG K K,KANG S C,PAENG K S,et al. Analysis of vibration of the turbine blades using non-intrusive stress measurement system[C]//ASME 2006 Power Conference,2006.
[13] 侯明,栾想,闫贺,等. 一种用于转子叶片叶尖定时法研究的装置设计及应用[J]. 测控技术,2024,43(8):29-36. HOU Ming,LUAN Xiang,YAN He,et al. Design and application of a device for study on rotor blades tip-timing method[J]. Measurement & Control Technology,2024,43(8):29-36.
[14] XU J,QIAO B,LIU J,et al. Sparse reconstruction for blade tip timing signal using generalized minimax- concave penalty[J]. Mechanical Systems and Signal Processing,2021,161:107961.
[15] LIN J,HU Z,CHEN Z S,et al. Sparse reconstruction of blade tip-timing signals for multi-mode blade vibration monitoring[J]. Mechanical Systems and Signal Processing,2016,81:250-258.
[16] BOUCHAIN A,PICHERAL J,LAHALLE E,et al. Blade vibration study by spectral analysis of tip-timing signals with OMP algorithm[J]. Mechanical Systems and Signal Processing,2019,130:108-121.
[17] LIU Z,DUAN F,NIU G,et al. Reconstruction of blade tip-timing signals based on the MUSIC algorithm[J]. Mechanical Systems and Signal Processing,2022,163:108137.
[18] 贺长波,李宏坤,赵新维,等. 基于总体最小二乘准则旋转不变子空间法的叶尖定时欠采样信号分析[J]. 机械工程学报,2019,55(19):103-111. HE Changbo,LI Hongkun,ZHAO Xinwei,et al. Analysis method for under-sampled blade tip-timing signal based on the rotational invariance technique with total least squares principle[J]. Journal of Mechanical Engineering,2019,55(19):103-111.
[19] 李孟麟,段发阶,欧阳涛,等. 基于叶尖定时的旋转机械叶片振动频率辨识ESPRIT方法[J]. 振动与冲击,2010,29(12):18-21,235. LI Menglin,DUAN Fajie,OUYANG Tao,et al. ESPRIT method for blade vibration frequency identification in rotating machinery based on blade tip-timing measurement[J]. Journal of Vibration and Shock,2010,29(12):18-21,235.
[20] WU S,ZHAO Z,YANG Z,et al. Physical constraints fused equiangular tight frame method for blade tip timing sensor arrangement[J]. Measurement,2019,145:841-851.
[21] WANG Z,YANG Z,WU S,et al. An improved multiple signal classification for nonuniform sampling in blade tip timing[J]. IEEE Transactions on Instrumentation and Measurement,2020,69(10):7941-7952.
[22] WANG Z,YANG Z,WU S,et al. Block-MUSIC in blade tip timing:Performance study of block snapshot matrix[J]. Mechanical Systems and Signal Processing,2023,198:110374.
[23] WANG Z,YANG Z,LI H,et al. Subspace dimension reduction for faster multiple signal classification in blade tip timing[J]. IEEE Transactions on Instrumentation and Measurement,2021,70:1-10.
[24] 汪松柏,郝玉扬,吴亚东,等. 航空发动机压气机旋转不稳定现象研究进展[J]. 航空学报,2024,45(16):6-26. WANG Songbai,HAO Yuyang,WU Yadong,et al. Research progress on rotating instability of aeroengine compressor[J]. Acta Aeronautica et Astronautica Sinica,2024,45(16):6-26.
[25] DOUGHERTY R P. Functional beamforming[C/CD]//Proceedings on CD of the 5th Berlin Beamforming Conference,February 19-20,2014.
[26] DOUGHERTY R P. Beamforming with modified steering vectors for jet noise source location[J]. International Journal of Aeroacoustics,2023,22(5-6):552-575.
[27] YANG Y,CHU Z,SHEN L,et al. Functional delay and sum beamforming for three-dimensional acoustic source identification with solid spherical arrays[J]. Journal of Sound and Vibration,2016,373:340-359.

旋转叶片固有频率识别：基于函数波束形成的叶尖定时信号频谱混叠抑制方法

Natural Frequency Identification of Rotating Blades: A Functional Beamforming-based Method for Spectral Aliasing Suppression in Blade Tip Timing Signals

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