• Semiconductor Optoelectronics
  • Vol. 44, Issue 3, 460 (2023)
ZHENG Weigang1、*, ZHAO Zhenwei1, TANG Hong1, ZHANG Zhongrui2, YANG Xin3, YANG Hongyue4, and MIAO Teng3
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
  • 3[in Chinese]
  • 4[in Chinese]
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    DOI: 10.16818/j.issn1001-5868.2023031203 Cite this Article
    ZHENG Weigang, ZHAO Zhenwei, TANG Hong, ZHANG Zhongrui, YANG Xin, YANG Hongyue, MIAO Teng. Automatic Detection Method for Tunnel Cable Laying Quality Parameters Based on Three-dimensional Laser Point Cloud[J]. Semiconductor Optoelectronics, 2023, 44(3): 460 Copy Citation Text show less

    Abstract

    Non-standard laying of power cables is the main cause of insulation failure, which affects the safe operation of cables. At present, the quality detection of cable laying mostly adopts manual contact measurement, which has strong subjectivity and low accuracy, and is easy to cause secondary damage to the laying area. In order to solve this problem, an automatic detection method of tunnel cable laying quality parameters based on point cloud is proposed. Firstly, the tunnel cable point cloud data was obtained at the cable laying construction position. After that, the cable point cloud was segmented based on the structural characteristics of the tunnel. Finally, the laying area was segmented from the cable point cloud based on color and morphological features, and the laying quality parameters were automatically measured. The average accuracy, recall rate and F1 score of the cable and laying area point cloud segmentation algorithm proposed in this study are all greater than 0.92, and the average absolute error of the four laying quality parameters measured automatically is less than 0.35 mm. Experiments show that this research method can accurately locate the cable laying area and automatically and accurately measure the laying quality parameters.
    ZHENG Weigang, ZHAO Zhenwei, TANG Hong, ZHANG Zhongrui, YANG Xin, YANG Hongyue, MIAO Teng. Automatic Detection Method for Tunnel Cable Laying Quality Parameters Based on Three-dimensional Laser Point Cloud[J]. Semiconductor Optoelectronics, 2023, 44(3): 460
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