叶端振动信号频谱分析的前后向平滑MUSIC法

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振动与冲击 ›› 2025, Vol. 44 ›› Issue (10) : 208-214.

航空航天

叶端振动信号频谱分析的前后向平滑MUSIC法

平艳1，王增坤*2,3，范志飞1，袁超1，杨志勃3，乔百杰3

作者信息 +

Forward and backward smoothing MUSIC method for spectrum analysis of blade tip vibration signal

PING Yan1,WANG Zengkun*2,3,FAN Zhifei1,YUAN Chao1,YANG Zhibo3,QIAO Baijie3

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摘要

叶端定时是航空发动机叶片叶端振动非接触测量的有效手段，但其采样模式决定了所采信号具有高度欠采样特征，需要进行抗混叠频谱分析从而提取转子叶片固有频率这一关键指标。利用了前向平滑策略的改进多重信号分类法（MUltiple SIgnal Classification，MUSIC）能实现抗混叠但无法充分发挥平滑方法的优势。因此，本文提出适用于叶端定时信号处理的前后向平滑MUSIC法，通过建立传感器的对称布局条件，利用前后向平滑方法代替前向平滑方法，得到更准确的自相关矩阵估计，进而提高叶片固有频率估计性能，并通过仿真和实验验证了在样本数量、算法参数等相同的情况下，前后向平滑MUSIC法的混叠与噪声抑制能力得到了提升。

Abstract

Blade tip timing (BTT) is an effective technique for non-contact vibration measurement of rotor blades of aeroengine, but its sampling pattern leads to the highly undersampled property of the sampled signals. Anti-aliasing spectrum analysis is required to extract the key indicator of the rotor blade, which is natural frequency. The improved multiple signal classification (MUSIC) method using the forward smoothing strategy can achieve anti-aliasing but cannot fully utilize the advantages of the smoothing method. Therefore, this paper proposes a forward-backward smoothing MUSIC method for BTT signal processing. By establishing the symmetrical placement conditions of the sensor, the forward-backward smoothing is used to replace the forward smoothing to obtain a more accurate autocorrelation matrix estimate, thereby improving the blade natural frequency estimation performance. Through simulation and experiments, it is verified that the aliasing and noise suppression capabilities of the forward-backward smoothing MUSIC method are improved under the same sample number, algorithm parameters, etc.

导出引用

平艳1, 王增坤2, 3, 范志飞1, 袁超1, 杨志勃3, 乔百杰3. 叶端振动信号频谱分析的前后向平滑MUSIC法[J]. 振动与冲击, 2025, 44(10): 208-214

PING Yan1, WANG Zengkun2, 3, FAN Zhifei1, YUAN Chao1, YANG Zhibo3, QIAO Baijie3. Forward and backward smoothing MUSIC method for spectrum analysis of blade tip vibration signal[J]. Journal of Vibration and Shock, 2025, 44(10): 208-214

参考文献

[1] 王维民,张旭龙,陈康,等. 大型轴流压气机叶片无键相振动监测与故障预警方法[J]. 振动与冲击, 2019, 38(23): 54-61.
WANG Weimin, ZHANG Xulong, CHEN Kang, et al. Vibration monitoring and fault pre-warning method for large axial compressor blades without OPR sensor[J]. Journal of Vibration and Shock, 2019, 38(23): 54-61.
[2] 范博楠，张玉波，王海斗，等. 基于叶尖定时技术的叶轮叶片动态监测研究现状[J]. 振动与冲击, 2016, 35(5): 96-102.
FAN Bonan, ZHANG Yubo, WANG Haidou, et al. Research State of Dynamic Monitoring for Blades of Impellers Based on Blade Tip-Timing[J]. Journal of Vibration and Shock, 2016, 35(5): 96-102.
[3] Hu D, Wang W, Zhang X, et al. On-line real-time mistuning identification and model calibration method for rotating blisks based on blade tip timing (BTT)[J]. Mechanical Systems and Signal Processing, 2021, 147: 107074.
[4] 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/OL].推进技术:1-14[2024-05-13].
ZHOU Kai, QIAO Bai-jie, LIU Mei-ru, et al. Blade Tip Timing Measurement Method without Once-Per-Revolution Sensor based on Dynamic Tracking of Reference Key Phase [J/OL]. Journal of Propulsion Technology: 1-14.
[5] 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.
[6] Liu Z, Duan F, Niu G, et al. An improved circumferential Fourier fit (CFF) method for blade tip timing measurements[J]. Applied Sciences, 2020, 10(11): 3675.
[7] Chen S, Yang Y, Hu H, et al. Blind interpolation for multi-frequency blade tip timing signals[J]. Mechanical Systems and Signal Processing, 2022, 172: 108946.
[8] 张继旺，唐雨，丁克勤，等. 稀疏度自适应匹配追踪的欠采样BTT信号重构方法[J]. 振动与冲击, 2023, 42(20): 286-292
ZHANG Jiwang, TANG Yu, DING Keqin, et al. Reconstruction of the blade tip-timing based on a modified sparsity adaptive matching pursuit algorithm[J]. Journal of Vibration and Shock, 2023, 42(20): 286-2929.
[9] 王永良.空间谱估计理论与算法[M]. 北京: 清华大学出版社,2004.
WANG Yongliang. Spatial spectrum estimation theories and algorithms[M]. Beijing: Tsinghua University Press, 2004.
[10] 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.
LI Menglin, DUAN Fajie, OUYANG Tao, et al. The ESPRIT Method for the Blade Vibration Frequency Identification of the Rotating Machinery from Blade Tip-Timing Measurement[J]. Journal of Vibration and Shock, 2010, 29(12): 18-21.
[11] 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.
[12] Wang P, Karg D, Fan Z, et al. Non-contact identification of rotating blade vibration[J]. Mechanical Engineering Journal, 2015, 2(3): 15-00025-15-00025.
[13] 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.
[14] Jin R, Yang L, Yang Z, et al. Improved minimum variance distortionless response spectrum method for efficient and robust non-uniform undersampled frequency identification in blade tip timing[J]. Frontiers of Mechanical Engineering, 2023, 18(4): 43.
[15] Pan J, Sun M, Wang Y, et al. Simplified spatial smoothing for DoA estimation of coherent signals[J]. IEEE Transactions on Circuits and Systems II: Express Briefs, 2022, 70(2): 841-845.
[16] Vo B N, Vo B T, Mahler R P S. Closed-form solutions to forward–backward smoothing[J]. IEEE Transactions on Signal Processing, 2011, 60(1): 2-17.
[17] Stoica P, Nehorai A. MUSIC, maximum likelihood, and Cramer-Rao bound: further results and comparisons[J]. IEEE Transactions on Acoustics, Speech, and Signal Processing, 1990, 38(12): 2140-2150.
[18] Wang Z K, Yang Z B, Wu S M, et al. Block-MUSIC in blade tip timing: Performance study of block snapshot matrix[J]. Mechanical Systems and Signal Processing, 2023, 198: 110374.