• Optics and Precision Engineering
  • Vol. 32, Issue 5, 661 (2024)
Chi WANG1, Peng CAO1, Qing HUANG2, Chao WANG1, and Cailiang SHENG3,*
Author Affiliations
  • 1Department of Precision Mechanical Engineering, Shanghai University, Shanghai200444, China
  • 2Aviation Industry Corporation of China Luoyang Electro-optical Equipment Research Institute, Luoyang47103, China
  • 3Jiangsu Yongkang Machinery Co., Ltd.,Wuxi21420, China
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    DOI: 10.37188/OPE.20243205.0661 Cite this Article
    Chi WANG, Peng CAO, Qing HUANG, Chao WANG, Cailiang SHENG. Acoustic-vibration intelligent detection of flexible shallow buried objects[J]. Optics and Precision Engineering, 2024, 32(5): 661 Copy Citation Text show less
    Imaging principle of laser shear speckle interferometer
    Fig. 1. Imaging principle of laser shear speckle interferometer
    Network structure of YOLOv5s
    Fig. 2. Network structure of YOLOv5s
    Slicing operation
    Fig. 3. Slicing operation
    Structure diagram of CSP
    Fig. 4. Structure diagram of CSP
    Sound-light fusion intelligent detection system of flexible shallow buried object
    Fig. 5. Sound-light fusion intelligent detection system of flexible shallow buried object
    Coach thunder shells and brick detection results
    Fig. 6. Coach thunder shells and brick detection results
    Detection effect to judge thunder shell
    Fig. 7. Detection effect to judge thunder shell
    Evaluation index
    Fig. 8. Evaluation index
    Detection effect for type determination of thunder
    Fig. 9. Detection effect for type determination of thunder
    F1 curve of flexible shallow buried objects category detection
    Fig. 10. F1 curve of flexible shallow buried objects category detection
    埋设目标几何参数外壳材质
    69式φ27 cm×8 cm工程塑料
    72式φ30 cm×6 cm橡胶
    58式φ11 cm×10 cm低碳钢
    砖块24 cm×12 cm×5.5 cm混凝土
    Table 1. Characteristic parameters of typical flexible shields
    探测目标土壤类型剪切量/mm埋设深度/mm声波频率/Hz声波分贝/dB
    69式细沙12.12210/30/50110120
    72式细沙10.93510/30/50
    58式细沙12.12210/30/50
    Table 2. Experimental environment and parameters for different buried depths of coach shell
    硬件/软件型号/版本
    处理器Inter(R)Xeon(R) CPU E5-2678 v3 @2.50GHz
    显卡NVIDIA GeForce RTX 2080Ti
    内存62G
    深度学习框架Pytorch 1.10.0(基于Python3.8)
    Table 3. Linux software and hardware configuration
    参 数
    Epochs300
    Batchsize48
    Nomentum0.937
    输入图像尺寸640×640
    初始的学习率0.01
    权重衰减系数0.0005
    Table 4. Training parameters setting
    Chi WANG, Peng CAO, Qing HUANG, Chao WANG, Cailiang SHENG. Acoustic-vibration intelligent detection of flexible shallow buried objects[J]. Optics and Precision Engineering, 2024, 32(5): 661
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