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基于LabVIEW软件平台的粗晶材料超声信号去噪处理的研究 被引量:1

LABVIEW PLATFORM BASED DE-NOISING PROCESSING OF ULTRASONIC SIGNAL OF COARSE-GRAINED MATERIALS
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摘要 采用超声纵波检测粗晶材料缺陷时,由于晶粒粗大及各向异性的影响,将产生较强的组织散射噪声,降低材料超声探伤的信噪比,严重干扰对缺陷回波的正确识别与判断。文章分析了粗晶材料超声信号去噪处理方法,提出了基于软件平台LabVIEW的信号处理构想,设计了粗晶材料超声信号去噪处理的LabVIEW处理模块,为有效抑制粗晶材料的组织散射噪声提供了手段。 When ultrasonic detection is used to inspect the defect of coarse-grained materials, serious structure-scattered noise will occur because of the influence of coarse grains,consequently the signal-to-noise ratio(SNR) is lowered and identification and judgment of defect signal is seriously disturbed. Signal processing design ideas based on the software LabVIEW are put forward after the de-noising processing method of ultrasonic signal of coarse-grained materials is analysed. The design of de-noising processing module on LabVIEW is also studied. and methods are offered for suppressing the structure-scattered noise in coarse-grained materials efficiently.
作者 张惠 刘晴岩
出处 《无损检测》 2004年第11期558-561,共4页 Nondestructive Testing
关键词 超声检测 粗晶材料 去噪 信号处理 Ultrasonic testing Coarse-grained material De-noising Signal processing
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参考文献3

  • 1Bilgutay NM, Bencharit U, Murthy R, et al. Analysis of a non-linear frequency diverse clutter suppression algorithm[J]. Ultrasonics, 1990,28(3): 90- 96.
  • 2Rose JL, et al. Utility of split-spectrum processing in ultrasonic nondestructive evaluation [J]. Materials Evaluation, 1988,46 (1): 114- 122.
  • 3Newhous VL, Bilgutay NM, Saniie J, et al. Flaw-tograin echo enhancement by split spectrum processing [J]. Ultrasonics, 1982,20(3): 59-68.

同被引文献3

  • 1孙宝申,沈建中.合成孔径聚焦超声成像(一)[J].应用声学,1993,12(3):43-48. 被引量:49
  • 2Fredrik LingvalI,Tomas Olofsson, "On Time -Domain Model -Based Ultrasonic Array Imaging",lEEE Transactions on Ultrasonics, Ferroelectrics,and Frequency Control, VOL54, NO8,August 2007.
  • 3E.Pignone, "Enhancement in image quality in ultrasonic flaw detection process in rotor turbine using SAFT", IEEE International Workshop on Imaging Systems and Techniques (IST 2004), Stresa, Italy, 14 May 2004.

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