Journals Articles Conferences News About CLP
Submit a paper Email Alert
Search
Search
Articles
Journals
News
Advanced Search
Top Searches
2D MaterialsTransformation opticsQuantum PhotonicsSmall lasersSemiconductor UV PhotonicsSupersymmetric microring laser arrays

Infrared and Laser Engineering, Volume. 53, Issue 10, 20240217(2024)

Non-contact infrared laser physical property inversion method for target surface based on SSA-GRNN

Ronghua LI1,2, Xinchen ZHOU1,2, Chuanxin WENG3, Haopeng XUE1,2, Jinlong WU1,2, and Chenyu LIN1,2
Author Affiliations
  • 1Institute of Mechanical Engineering, Dalian Jiaotong University, Dalian 116028, China
  • 2Advanced Robot Sensing and Control Technology Innovation Center, Dalian 116028, China
  • 3Beijing Institute of Environmental Characteristics, Beijing 100854, China
    • show less
    AbstractGet PDF(in Chinese)
    Figures&Tables (14)
    Equations (19)
    References (17)
    Tools
    Paper Information
    Topics
    Figures & Tables(14)
    Flowchart of the physical inversion method

    Fig. 1. Flowchart of the physical inversion method

    Download full size
    View in Article
    Neural network model of GRNN

    Fig. 2. Neural network model of GRNN

    Download full size
    View in Article
    Physical inversion process

    Fig. 3. Physical inversion process

    Download full size
    View in Article
    Target to be tested

    Fig. 4. Target to be tested

    Download full size
    View in Article
    Echo intensity measurements of different materials at the same distance

    Fig. 5. Echo intensity measurements of different materials at the same distance

    Download full size
    View in Article
    Echo intensity measurement results at different distances with the same material

    Fig. 6. Echo intensity measurement results at different distances with the same material

    Download full size
    View in Article
    Measurement system for laser echo intensity (1-Laser driver; 2-Detector drive; 3-Target to be tested; 4-Detectors; 5-Infrared laser emitter; 6-Turntable; 7-Oscilloscope)

    Fig. 7. Measurement system for laser echo intensity (1-Laser driver; 2-Detector drive; 3-Target to be tested; 4-Detectors; 5-Infrared laser emitter; 6-Turntable; 7-Oscilloscope)

    Download full size
    View in Article
    Experimental program

    Fig. 8. Experimental program

    Download full size
    View in Article
    Comparison between output values and actual values of different materials

    Fig. 9. Comparison between output values and actual values of different materials

    Download full size
    View in Article
    Inversion probabilities of SSA-GRNN and GRNN prediction models at different distances

    Fig. 10. Inversion probabilities of SSA-GRNN and GRNN prediction models at different distances

    Download full size
    View in Article

    • Table 1. Parameters of the target to be tested

      View table
      View in Article

      Table 1. Parameters of the target to be tested

      ParameterProperties
      SurfacePolyimideOriginalPaint
      SubstrateSteel& foilSteelSteel
      Reflection typeSpecularSemi specularDiffuse

    • Table 2. Evaluation of laser echo intensity model indicators

      View table
      View in Article

      Table 2. Evaluation of laser echo intensity model indicators

      Evaluating indicatorEMAEMSERMS
      SSA-GRNNTraining set0.63151.76051.3268
      Test set0.30361.84691.3590
      GRNNTraining set13.6392548.399423.4179
      Test set3.4873147.839712.1589

    • Table 3. Laser echo intensity data of unknown material surface

      View table
      View in Article

      Table 3. Laser echo intensity data of unknown material surface

      No.Material 1: PolyimideMaterial 2: SteelMaterial 3: WhiteMaterial 4: RedMaterial 5: BlueMaterial 6: Black
      13.09, 1.0, 80.52.81, 1.0, 1272.77, 1.0, 141.12.97, 1.0, 110.62.93, 1.0, 45.72.99, 1.0, 15.4
      22.91, 1.0, 168.32.75, 1.0, 145.52.63, 1.0, 153.62.81, 1.0, 158.52.75, 1.0, 70.52.75, 1.0, 38.1
      32.37, 1.0, 106.22.51, 1.0, 109.82.49, 1.0, 112.52.51, 1.0, 144.52.61, 1.0, 64.12.51, 1.0, 22.5
      42.77, 1.2, 119.32.73, 1.2, 69.32.57, 1.2, 119.82.79, 1.2, 76.22.77, 1.2, 22.12.83, 1.2, 7.8
      52.27, 1.2, 136.62.59, 1.2, 117.92.37, 1.2, 106.52.55, 1.2, 131.62.65, 1.2, 43.22.59, 1.2, 24.8
      62.19, 1.2, 91.12.37, 1.2, 94.92.31, 1.2, 84.32.39, 1.2, 118.32.39, 1.2, 62.32.29, 1.2, 15.5
      72.71, 1.4, 101.22.61, 1.4, 63.92.61, 1.4, 81.92.65, 1.4, 79.82.63, 1.4, 28.92.69, 1.4, 9.6
      82.65, 1.4, 141.72.51, 1.4, 91.22.45, 1.4, 118.92.51, 1.4, 125.32.45, 1.4, 57.62.43, 1.4, 22.1
      92.11, 1.4, 134.32.25, 1.4, 73.42.25, 1.4, 103.92.23, 1.4, 104.22.19, 1.4, 41.52.15, 1.4, 14.1
      102.49, 1.5, 135.32.38, 1.5, 54.62.62, 1.5, 34.32.49, 1.5, 70.12.57, 1.5, 27.92.53, 1.5, 9.9
      112.11, 1.5, 149.72.12, 1.5, 47.72.33, 1.5, 82.52.41, 1.5, 87.52.43, 1.5, 46.12.39, 1.5, 18.2
      122.05, 1.5, 112.22.04, 1.5, 35.282.19, 1.5, 73.82.07, 1.5, 55.62.13, 1.5, 36.52.11, 1.5, 13.7
      132.59, 1.6, 32.52.47, 1.6, 30.12.43, 1.6, 45.52.47, 1.6, 43.92.45, 1.6, 14.32.45, 1.6, 9.1
      142.47, 1.6, 72.12.29, 1.6, 55.62.31, 1.6, 62.72.35, 1.6, 67.12.27, 1.6, 28.82.25, 1.6, 18.8
      151.93, 1.6, 62.42.05, 1.6, 41.82.03, 1.6, 53.11.97, 1.6, 57.92.15, 1.6, 30.91.83, 1.6, 6.9
      162.27, 2.0, 14.62.13, 2.0, 10.12.07, 2.0, 12.62.03, 2.0, 15.392.05, 2.0, 6.92.15, 2.0, 2.2
      172.15, 2.0, 27.42.03, 2.0, 15.71.99, 2.0, 19.21.85, 2.0, 28.61.89, 2.0, 13.41.93, 2.0, 6.25
      181.37, 2.0, 9.31.87, 2.0, 26.11.87, 2.0, 26.731.65, 2.0, 21.871.75, 2.0, 15.51.53, 2.0, 5.4

    • Table 4. Inversion results of SSA-GRNN model for material 1

      View table
      View in Article

      Table 4. Inversion results of SSA-GRNN model for material 1

      No.Angle/(°)Distance/mmSSA-GRNNGRNN
      Predicted intensityEsquaredPredicted materialPredicted intensityEsquaredPredicted material
      13.09100079.1651.782178.4034.3974
      22.911000173.38525.8571172.84420.6481
      32.371000108.5265.41192.871177.6624
      42.771200120.2540.911129.98114.0621
      52.271200133.7987.8511135.9730.3931
      62.19120088.4716.912179.392137.0774
      72.711400102.1070.823172.516822.7724
      82.651400141.9430.0591155.155181.0371
      92.111400127.93440.5261126.84555.5771
      102.59160032.7720.074129.23310.6733
      112.47160072.5330.188180.71774.2531
      121.93160061.3221.162147.546220.6414
      132.272 00014.3090.085112.0236.6412
      142.152 00026.6900.504137.38499.681
      151.372 0009.8060.256110.8072.2714
    Tools

    Get Citation

    Copy Citation Text

    Ronghua LI, Xinchen ZHOU, Chuanxin WENG, Haopeng XUE, Jinlong WU, Chenyu LIN. Non-contact infrared laser physical property inversion method for target surface based on SSA-GRNN[J]. Infrared and Laser Engineering, 2024, 53(10): 20240217

    Download Citation

    EndNote(RIS)BibTexPlain Text
    Set citation alerts for article
    Save article for my favorites
    Paper Information

    Category: 光电测量

    Received: May. 17, 2024

    Accepted: Jul. 31, 2024

    Published Online: Dec. 13, 2024

    The Author Email:

    DOI:10.3788/IRLA20240217

    Topics

    laser devices and laser physics
    Lasers and Laser Optics
    Laser physics
    laser manufacturing
    Instrumentation, Measurement and Metrology