Acta Optica Sinica, Volume. 38, Issue 7, 0712003(2018)

Detection and Evaluation of Surface Defects Based on Critical Frequency Method by Laser Ultrasonic

Haiyang Li1、*, Qiaoxia Li1, Zhaoba Wang1, and Qianghua Pan2
Author Affiliations
  • 1 School of Information and Communication Engineering, North University of China, Taiyuan, Shanxi 0 30051, China
  • 2 China Special Equipment and Research Institute, Beijing 100029, China
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    Figures & Tables(18)
    Scattering effect between surface wave and defect
    Experimental diagram
    Laser ultrasonic platform
    Experimental samples
    Sample size
    Direct wave spectrum diagram
    B-scanning images of surface defect. (a) Defect depth of 0.40 mm; (b) defect depth of 0.30 mm; (c) defect depth of 0.20 mm; (d) defect depth of 0.10 mm; (e) defect depth of 0.08 mm
    Frequency spectrum energy diagrams of reflection/transmission signals. (a) Defect depth of 0.40 mm; (b) defect depth of 0.30 mm; (c) defect depth of 0.20 mm; (d) defect depth of 0.10 mm; (e) defect depth of 0.08 mm (red solid lines and blue solid lines represent curves of transmission surface wave and defect reflection surface wave, respectively)
    Relationship between surface defect depth and corresponding wavelength
    B-scanning images at different distances between excitation point and detection point
    Frequency spectrum energy diagrams of reflection/transmission signal when distance between excitation point and detection point is different. (a) Distance of 5 mm; (b) distance of 10 mm ; (c) distance of 15 mm; (d) distance of 20 mm; (e) distance is of 25 mm (the red solid lines and blue solid lines represent curves of transmission surface wave and defect reflection surface wave, respectively)
    Samples with different materials. (a) Steel sample; (b) aluminum sample
    Frequency spectrum energy diagrams of reflection/transmission signals of samples with different materials. (a) Aluminum; (b) steel (the red solid lines and blue solid lines represent curves of transmission surface wave and defect reflection surface wave, respectively)
    • Table 1. Defect depth

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      Table 1. Defect depth

      SampleDefect depth /mm
      A0.40
      B0.30
      C0.20
      D0.10
      E0.08
    • Table 2. Measured location and error of defects

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      Table 2. Measured location and error of defects

      SampleDefect location /mmError /%
      A6.74.2
      B6.91.4
      C6.91.4
      D7.11.4
      E7.11.4
    • Table 3. Measured defect depth and error

      View table

      Table 3. Measured defect depth and error

      Sample defect depth /mmFrequency /MHzWavelength /mmMeasured defect depth /mmError /%
      0.401.821.6020.4010.25
      0.302.601.1220.2816.33
      0.203.390.8600.2157.50
      0.107.600.3840.0964.00
      0.089.500.3070.0773.75
    • Table 4. Measured defect depth and error at different distances between excitation point and detection point

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      Table 4. Measured defect depth and error at different distances between excitation point and detection point

      Distance /mmFrequency /MHzWavelength /mmMeasured defect depth /mmError /%
      51.961.4880.3727.00
      101.871.5590.3902.50
      151.711.7050.4266.50
      201.851.5760.3941.50
      251.791.6290.4071.75
    • Table 5. Defect depth and error of samples with different materials

      View table

      Table 5. Defect depth and error of samples with different materials

      MaterialSample defect depth /mmFrequency /MHzWavelength /mmMeasured defect depth /mmError /%
      Aluminum0.401.871.5590.3902.50
      Steel0.401.851.5140.3795.25
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    Haiyang Li, Qiaoxia Li, Zhaoba Wang, Qianghua Pan. Detection and Evaluation of Surface Defects Based on Critical Frequency Method by Laser Ultrasonic[J]. Acta Optica Sinica, 2018, 38(7): 0712003

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    Paper Information

    Category: Instrumentation, Measurement and Metrology

    Received: Dec. 5, 2017

    Accepted: --

    Published Online: Sep. 5, 2018

    The Author Email: Li Haiyang (climb021@163.com)

    DOI:10.3788/AOS201838.0712003

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