Underdetermined Blind Source Separation of Aeroengine Vibration Signal Mixtures

Journal of Propulsion Technology ›› 2014, Vol. 35 ›› Issue (4): 552-558.

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Underdetermined Blind Source Separation of Aeroengine Vibration Signal Mixtures

Department of Airborne Vehicle Engineering, Naval Aeronautical Engineering Institute, Yantai 264001, China;Department of Airborne Vehicle Engineering, Naval Aeronautical Engineering Institute, Yantai 264001, China;Department of Electronic and Information Engineering, Naval Aeronautical Engineering Institute, Yantai 264001, China;Department of Navy Aviation Technology Guarantee, Beijing 100074, China;Department of Airborne Vehicle Engineering, Naval Aeronautical Engineering Institute, Yantai 264001, China;Department of Airborne Vehicle Engineering, Naval Aeronautical Engineering Institute, Yantai 264001, China

Published:2021-08-15

航空发动机混叠振动信号的欠定盲源分离方法

张赟¹,李本威¹,贾舒宜²,王子斌³,孙涛¹,杨欣毅¹

海军航空工程学院飞行器工程系,山东烟台 264001;海军航空工程学院飞行器工程系,山东烟台 264001;海军航空工程学院电子信息工程系,山东烟台 264001;海军装备航空技术保障部,北京 100074;海军航空工程学院飞行器工程系,山东烟台 264001;海军航空工程学院飞行器工程系,山东烟台 264001

作者简介:张赟(1983—),男,博士,讲师,研究领域为航空发动机测试与故障诊断。E-mail:hjhy_zy@126.com
基金资助:
军队科研基金项目(5130704023)。

Abstract

Abstract: Aimed at the problem that the conventional underdetermined blind source separation (UBSS) methods are difficult to deal with the delayed aero-engine vibration mixture signals, an underdetermined blind source separation with delays was researched by using the sparse component analysis. The number of sources and attenuation matrix were estimated by clustering mixture signals magnitude on the line direction. The delay matrix was obtained by recovering the cluster of signals real. The experiment results show that the different vibration sources of aero-engine vibration mixture signals were separated effectively under the condition that the number of sensors is less than that of sources.

Key words: Underdetermined blind source separation; Aero-engine; Vibration signal; Delayed mixture

摘要： 针对传统欠定盲源分离方法难以有效处理具有时间延迟效应的发动机混叠振动信号分离问题,采用稀疏分量分析法研究了一种时间延迟混合信号的欠定盲源分离方法。该方法通过对混合信号的频域模值的线性聚类分析实现源数目及衰减矩阵的估计,并通过恢复混合信号的频域实部在混合空间的聚类性推断出时间延迟矩阵。实验结果表明,该方法在欠定条件下(传感器个数小于振动源个数)能够有效地将发动机混叠振动信号按照不同的激振源进行分离。 

关键词: 欠定盲源分离;航空发动机;振动信号;时间延迟混合 

ZHANG Yun, LI Ben-wei, JIA Shu-yi, WANG Zi-bin, SUN Tao, YANG Xin-yi. Underdetermined Blind Source Separation of Aeroengine Vibration Signal Mixtures[J]. Journal of Propulsion Technology, 2014, 35(4): 552-558.

张赟,李本威,贾舒宜,王子斌,孙涛,杨欣毅. 航空发动机混叠振动信号的欠定盲源分离方法[J]. 推进技术, 2014, 35(4): 552-558.

References

[1] Gelle G, Colas M, Delaunay G.Blind Sources Separation Applied to Rotating Machines Monitoring by Acoustical and Vibration Analysis[J].Mechanical Systems and Signal Processing, 2000,4(13):427-442.
[2] Roan M J, Ering J G, Sibul L H.A New, Nonlinear, Adaptive, Blind source Separation Approach to Gear Tooth Feature Detection and Analysis[J].Mechanical Systems and signal Processing, 2002,6(5):719-740.
[3] Serviere C, Fabry P.Blind Source Separation of Noisy Harmonic Signals for Rotating Machine Diagnosis[J].Journal of Sound and Vibration, 2004,2:317-339.
[4] 李舜酩.转子振动故障信号的盲分离[J].航空动力学报, 2005,0(5):752-756.
[5] 宋晓萍, 廖明夫.双转子航空发动机振动信号的分离测试技术[J].机械科学与技术, 2006,5(4).
[6] Li Y, Cichocki A, Amari S.Sparse Component Analysis for Blind Source Separation with Less Sensors Than Sources[C].Japan:4th International Symposium on Independent Component Analysis and Blind Signal Separation (ICA2003), 2003.
[7] Zibulevsky M, Pearlmutter B A.Blind Source Separation by Sparse Decomposition in a Signal Dictionary[J].Neural Computation, 2001,3(4):863-882.
[8] Bofill P.Underdetermined blind separation of Delayed Sound Sources in the Frequency Domain[R].Technical Report UPC-DAC-2001-14.
[9] Lee T W, Lewicki M S, Girolami M, et al.Blind Source Separation of More Sources Than Mixtures Using Overcomplete Representation[J].IEEE Signal Process Letter, 1999,6(4):87-90.
[10] Lewicki M S, Sejnowski T J.Learning Overcomplete Representations[J].Neural Computation, 2000,2:337-365.
[11] Abrard F, Deville Y.A Time-Frequency Blind Signal Separation Method Applicable to Underdetermined Mixtures of Dependent Sources[J].Signal Processing, 2005,5:1389-1403.
[12] Yilmaz O, Rickard S.Blind Separation of Speech Mixtures Via Time-Frequency Masking[J].IEEE Trans on Signal Processing.2006,2(7):1830-1847.
[13] 张赟, 李本威, 王永华.基于位势函数的欠定盲源分离识别诊断方法[J].航空动力学报, 2010,5(1), 218-223.
[14] Pearlmutter B A, Potluru V K.Sparse Separation:Principles and Tricks[C].Orlando:Proc SPIE volume 5102.Independent Component Analyses, Wavelets, and Neural Networks, 2003,1-4.
[15] 何昭水, 谢胜利, 傅予力.稀疏表示与病态混叠盲分离[J].中国科学, E辑, 2006,6(8):864-879.
[16] Bofill P, Zibulevsky M.Underdetermined Blind Source Separation Using Sparse Representations[J].Signal Processing, 2001,1:2353-2362.
[17] Lobo M S, Vandenberghe L, Boyd S.Applications of Second-order Cone Programming[J].Linear Algebra and its Applications, 1998,4:193-228.

Underdetermined Blind Source Separation of Aeroengine Vibration Signal Mixtures

航空发动机混叠振动信号的欠定盲源分离方法

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