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<p>Geometric quality control of multiple steel embedded plates is crucial for the performance and durability of nuclear power equipment during construction. Traditional manual measurement methods are cumbersome and inefficient. This study presents an automated geometry evaluation system that integrates camera and LiDAR fusion for improved accuracy. To tackle the challenge of localizing multi-embedded steel plates in tilted images, we propose a novel coarse-to-fine localization approach with tilt correction. For point cloud alignment and data mapping, we introduce a target-free camera and LiDAR calibration method that enables precise geometric extraction of the plates. The proposed system, which incorporates edge computing, has been validated in field tests, demonstrating high efficiency (3&#xa0;min) and reliability (1.81&#xa0;mm accuracy).</p>

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Automatic geometric quality evaluation of multiple embedded plates based on target-free LiDAR and camera fusion

  • 期刊论文

  • 发表日期：

    2025年2月28日

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  • Hangyu Li,
  • Weibing He,
  • Yizhi Shan,
  • Shang Yang,
  • Yan Xu,
  • Jian Zhang

摘要

Geometric quality control of multiple steel embedded plates is crucial for the performance and durability of nuclear power equipment during construction. Traditional manual measurement methods are cumbersome and inefficient. This study presents an automated geometry evaluation system that integrates camera and LiDAR fusion for improved accuracy. To tackle the challenge of localizing multi-embedded steel plates in tilted images, we propose a novel coarse-to-fine localization approach with tilt correction. For point cloud alignment and data mapping, we introduce a target-free camera and LiDAR calibration method that enables precise geometric extraction of the plates. The proposed system, which incorporates edge computing, has been validated in field tests, demonstrating high efficiency (3 min) and reliability (1.81 mm accuracy).