期刊文献+

超声导波信号形态分量分析方法研究 被引量:6

Study of Ultrasonic Guided Waves Signal Based on Morphology Component Analysis Method
下载PDF
导出
摘要 超声导波无损检测技术由于其传播距离远、检测范围大等优良性能,被广泛应用于航空航天、油气管道、压力容器等领域的检测.由于沿波导的长距离传播,超声导波除了有一般体波的特点外,还具有频散和多模态特性,该特性极大地限制了超声导波的检测效果,增大了特征识别的困难.开展针对超声导波频散和多模态特性的研究具有重要的理论和现实意义.本文通过分析超声导波频散和多模态特性的特点,提出从导波信号处理角度出发,采用形态分量分析的信号处理技术,深入研究导波信号的形态分解问题,并通过实验信号对方法的有效性进行了验证,为解决频散和多模态的影响以及为复杂导波信号的分析提供关键技术. Ultrasonic guided waves were widely used in aeronautics,pipeline,vessels and so on,because of its long distance propagation and large range detection property.Due to the long distance propagation along waveguides,the guided waves were not only possess the feature of ultrasonic bulk waves,but also dispersion and multimodes characters,which limited detection effect of guided waves and increased the difficulty of feature recognition.It has great theoretical and realistic sense to research the dispersion and multi-modes for ultrasonic guided waves.In this paper,the characters of dispersion and multi-modes were analyzed carefully,and a signal processing point of view was considered.The modeling and morphology decomposition of guided waves signals were proposed by the use of morphology component analysis techniques.The validations of these methods were realized through experiments.All of research results can provide key technologies for decreasing the effect of dispersion and multi-modes and analyzing complex for guided waves signals.
出处 《电子学报》 EI CAS CSCD 北大核心 2013年第3期444-450,共7页 Acta Electronica Sinica
基金 四川省应用基础研究(N.o2010JY005) 成都市科技局创新基金(No.11DXYB281JH-027)
关键词 超声导波 无损检测 频散 多模态 形态分量分析 ultrasonic guided waves nondestructive testing & evaluation dispersion multi modes morphology component analysis
  • 相关文献

参考文献27

  • 1M Petro. Ultrasonic guided waves in bone[J] .IEEE Transac- tions on Ultrasonics, Ferroelectrics, and Frequency Control, 2008,55(6) : 1277 - 1286.
  • 2S J Jin. Subset study on ullrasonic guided waves in fluid-filled pipes surrounded by water[J]. Mathematical Problems in Engi- neering, 2003,51 (3) : 760 - 770.
  • 3L Cohen. Time-frequency distributions-a review [ J ]. Proc IEEE, 1989,77(7) :941 - 981.
  • 4L Cohen. Time-Frequency Analysis: Theory and Applications [M]. NewYork: Prentice Hall, 1995.55 - 71.
  • 5L Atlas,P Duhamel. Recent developments in the core of digital signal processing[ J]. IEEE. Signal Processing Magazine, 1999,16(1):16- 31.
  • 6S Qian,D Chen. Joint time-frequency analysis[ J].IEEE, Signal Processing Magazine, 1999,16(2) :52 - 67.
  • 7S Qian. Introduction to Time-Frequency and Wavelet Trans- forms[ M]. NewYork: Prentice HaU, 2002.77 - 89.
  • 8周正干,冯占英,高翌飞,朱譞.时频分析在超声导波信号分析中的应用[J].北京航空航天大学学报,2008,34(7):833-837. 被引量:11
  • 9H Kwun, K A Bartels, C Dynes. Dispersion of longitudinal waves propagating in liquid-filled cylindrical shells[ J]. Journal of the Acoustical Society of America, 1999, 105(5) : 2601 - 2611.
  • 10何存富,李颖,王秀彦,吴斌,李隆涛.基于小波变换及Wigner-Ville变换方法的超声导波信号分析[J].实验力学,2005,20(4):584-588. 被引量:8

二级参考文献55

  • 1周廷方,汤锋,王进,王章野,彭群生.基于径向基函数的图像修复技术[J].中国图象图形学报(A辑),2004,9(10):1190-1196. 被引量:23
  • 2焦李成,孙强.多尺度变换域图像的感知与识别:进展和展望[J].计算机学报,2006,29(2):177-193. 被引量:45
  • 3陈益,李书.改进的小波阈值消噪法应用于超声信号处理[J].北京航空航天大学学报,2006,32(4):466-470. 被引量:41
  • 4A Hyvarinen, J Karhunen, E Oja. Independent component analysis[M]. New York: Wiley, 2001.
  • 5A Belouchrani,K A Merairn, J-F Cardoso, E Moulines. A blind source separation technique based on second order statistics[ J]. reEF, transactions on Signal Processing, 1997, 45 (2) : 434 - 444.
  • 6B A Pearlrnutter, V K Potluru. Sparse separation:Principles and tricks[ A]. Proceedings of International Society for Optical Engineering(SPIE) [ C]. Orlando, FL, USA,2003,5102:1 - 4.
  • 7P G Georgiev,F Theis,A Cichocki. Sparse component analysis and blind source separation of underdetermined mixtures [ J]. IEEE Transactions on Neural Network, 2005, 16 ( 4 ) : 992 - 996.
  • 8M Zibulevsky, B A Pearlmutter. Blind source separation by sparse decomposition in a signal dictionary [J ]. Neural Computation,2001,13(4) : 863 - 882.
  • 9J L Starck, M Elad, D Donoho. Redundant multiscale transforms and their application for morphological component analysis[J]. Advances in Imaging and Electron Physics, 2004, 132 (82) : 287 - 348.
  • 10J L Starck, M Elad, D Donoho. Image decomposition via the combination of sparse representation and a variational approach [J]. IEEE Transactions on Image Processing, 2005, 14( 10): 1570- 1582.

共引文献75

同被引文献41

引证文献6

二级引证文献11

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部