伪多源采样复域FastICA冲击定位算法

袁梅; 牛奔; 董韶鹏; 喻亮

doi:10.13700/j.bh.1001-5965.2015.0096

伪多源采样复域FastICA冲击定位算法

doi: 10.13700/j.bh.1001-5965.2015.0096

袁梅^1,2, ,,
牛奔^1,3,
董韶鹏¹,
喻亮¹

1.
北京航空航天大学自动化科学与电气工程学院, 北京 100083
2. 先进航空发动机协同创新中心, 北京 10008
3. 北京航空航天大学航空科学与技术国家实验室(筹), 北京 100083

基金项目: 国家自然科学基金(51375030)

详细信息

作者简介:
袁梅女,博士,副教授。主要研究方向:结构健康监测技术、信号处理技术、嵌入式系统及自动测试技术、先进传感技术、检测技术及自动化装置等。Tel.:010-82338757 E-mail:yuanm@buaa.edu.cn;牛奔男,硕士研究生。主要研究方向:信号处理。Tel.:010-82338757 E-mail:nb0128@buaa.edu.cn

通讯作者:
袁梅,Tel.:010-82338757 E-mail:yuanm@buaa.edu.cn

中图分类号: V219;TN911.7
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- 被引次数: 0
出版历程
- 收稿日期: 2015-02-13
- 网络出版日期: 2016-02-20

Pseudo-multi-source-sampling complex domain FastICA for impact location

YUAN Mei^{1,2
, ,},
NIU Ben^1,3,
DONG Shaopeng¹,
YU Liang¹

1.
School of Automation Science and Electrical Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100083, China
2. Collaborative Innovation Center for Advanced Aero-Engine, Beijing 10008
3. Aviation Science and Technology National Laboratory(Preparation), Beijing University of Aeronautics and Astronautics, Beijing 100083, China

摘要

摘要: 使用传感器阵列对材料结构冲击损伤进行定位,有助于及时发现损伤及潜在威胁,保障结构安全性。采用盲源分离(BSS)对传感器阵列信号进行预处理,提出单通道伪多源采样方法,利用每个传感器的分时段信息构建该传感器多源观测信号作为复域FastICA算法的输入,分离出每个传感器观测到的带有相位信息的冲击信号;结合阈值时延定位方法求解平面冲击事件的坐标。理论推导和数值仿真验证了本文设计的联合冲击定位算法的有效性。冲击定位平台上的实验结果表明,联合冲击定位算法可以从冲击-振动混合信号中分离出冲击信号,提高阵列传感器冲击定位的时延分析准确性。同时对传感器数量少于源信号的欠定BSS问题提供了一种解决方案。
- 盲源分离(BSS) /
- 独立分量分析 /
- 信号处理 /
- 冲击定位 /
- 单通道伪多源采样法
Abstract: Using the sensor array to locate impact can help to detect damage and its potential threats for structure materials, and to ensure structural safety. Sensor array signals are preprocessed by blind source separation (BSS). A single-channel pseudo-multi-source-sampling method is proposed, and data sequences of one sensor in different periods are used as multi-source observation signals of this sensor. The signals of all sensor arrays are used as inputs of complex domain FastICA impact extraction algorithm. Shock signals with phase information are separated from each sensor. The coordinates of impact events on test plane are solved by using the threshold time delay localization method. theoretical analysis and numerical simulation verify the effectiveness of the combined impact location algorithm. Experiment on the impact location platform shows that designed algorithm can separate out the impact from the signals mixed with vibration. It is suggested that the algorithm improves the precision of time delay analysis for impact location in the sensor array. It also provides a practicable solution for the underdetermined blind source separation problem while the number of sensors is less than the sources.
- blind source separation (BSS) /
- independent component analysis /
- signal processing /
- impact location /
- single-channel pseudo-multi-source-sampling method

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参考文献(15)

[1]	DERRISO M M,CHANG F K.Future roles of structural sensing for aerospace applications:RTO-MP-AVT-141[R].Neuilly-sur-Seine:Air Force Research Lab Wright Patterson Afb Oh Air Vehicles Directorate,2006.
[2]	苏永振,袁慎芳.基于独立分量分析的多源冲击定位方法[J].振动与冲击,2009,28(8):134-137. SU Y Z,YUAN S F.Impact of multi-source localization method based on independent component analysis[J].Journal of Vibration and Shock,2009,28(8):134-137(in Chinese).
[3]	IHN J B,CHANG F K.Pitch-catch active sensing methods in structural health monitoring for aircraft structures[J].Structural Health Monitoring,2008,7(1):5-19.
[4]	耿荣生,沈功田,刘时风.基于波形分析的声发射信号处理技术[J].无损检测,2002,24(6):257-261. GENG R S,SHEN G T,LIU S F.Acoustic emission signal processing technology based on waveform analysis[J].Nondestructive Testing,2002,24(6):257-261(in Chinese).
[5]	鲍鹏宇. 结构损伤监测信号处理方法研究[D].北京:北京航空航天大学,2013:65-82. BAO P Y.Research on methodology of structural damage monitoring signal processing[D].Beijing:Beihang University,2013:65-82(in Chinese).
[6]	李舜酩. 振动信号的盲源分离技术及应用[M].北京:航空工业出版社,2011:24-42. LI S M.Blind source separation vibration signal technology and applications[M].Beijing:Aviation Industry Press,2011:24-42(in Chinese).
[7]	LIM Y,LEE J,OH H S,et al.Independent component regression for seasonal climate prediction:An efficient way to improve multimodel ensembles[J].Theoretical and Applied Climatology,2015,119(3-4):433-441.
[8]	ZHANG X,VIALATTE F B,CHEN C,et al.Embedded implementation of second-order blind identification (SOBI) for real-time applications in neuroscience[J].Cognitive Computation,2015,7(S1):56-63.
[9]	CASTELLA M,MOREAU E,ZARZOSO V.Advances in heuristic signal processing and applications[M].Berlin:Springer,2013:183-217.
[10]	COMON P,JUTTEN C.Handbook of blind source separation:Independent component analysis and applications[M].New York:Academic Press,2010:179-207.
[11]	BINGHAM E,HYVÄRINEN A.A fast fixed-point algorithm for independent component analysis of complex valued signals[J].International Journal of Neural Systems,2000,10(1):1-8.
[12]	KUNDU T. Acoustic source localization[J].Ultrasonics,2014,54(1):25-38.
[13]	CHEN J,HUANG Y,BENESTY J.Time delay estimation[M]//HUANG Y,BENESTY J.Audio signal processing for next-generation multimedia communication systems.Berlin:Springer,2004:197-227.
[14]	KNAPP C H,CARTER G C.The generalized correlation method for estimation of time delay[J].IEEE Transactions on Acoustics,Speech and Signal Processing,1976,24(4):320-327.
[15]	CORRAL J L,MARTI J,REGIDOR S,et al.Continuously variable true time-delay optical feeder for phased-array antenna employing chirped fiber grating[J].IEEE Transactions on Microwave Theory and Techniques,1997,45(8):1531-1536.