| 王放,赵春菊,喻葭临,段斌,刘全,周宜红.考虑堆叠遮挡的堆石料级配视觉智能推理方法[J].水利学报,2025,56(10):1292-1303 |
| 考虑堆叠遮挡的堆石料级配视觉智能推理方法 |
| Visual intelligent inference method for material gradation in rockfill dams considering stacking occlusion |
| 投稿时间：2024-12-16 修订日期：2025-09-03 |
| DOI：10.13243/j.cnki.slxb.20240827 |
| 中文关键词: 堆石坝 堆叠遮挡 轮廓感知 尺寸估计 级配推理 |
| 英文关键词: rockfill dam stacking occlusion contour perception size estimation gradation inference |
| 基金项目:湖北工业大学高层次人才科研启动基金项目（XJ2022000201） |
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| 中文摘要: |
| 自然堆叠状态下的石料存在表层的粒间遮挡和深层的层间遮挡，会造成视觉信息损失，给级配视觉检测带来挑战。为此，本文提出考虑堆叠遮挡的堆石料级配视觉智能推理框架：通过构建自然堆叠状态下的石料颗粒视觉轮廓感知模型，重构受粒间遮挡的石块轮廓，并提取其特征参数；考虑堆叠角度的不确定性，基于随机颗粒形状和堆叠角度抽样估计其三维尺寸，实现了堆石料表层视觉级配评价；考虑层间遮挡造成的视觉级配与实际级配之间的差异，利用支持向量回归算法建立二者的关系映射，实现了考虑堆叠遮挡的堆石料实际级配推理。依托某水电站工程，通过现场实验验证了本文级配推理方法的可行性和有效性。研制部署的软硬件系统应用于工程级配检测，结果与筛分法高度一致。与传统筛分法相比，该系统干扰少、非接触，单次检测耗时在1 min内，过渡料和上游堆石料检测频次分别提升75和250倍，可实现上坝前的大规模石料级配高效、高精度的检测。 |
| 英文摘要: |
| In naturally stacked rock heaps，surface rocks not only occlude one another but also experience interlayer occlusion with deeper layers，resulting in visual information loss and significant challenges for accurate visual gradation detection. To address these challenges，this study proposes a vision-based intelligent inference framework for rockfill gradation that accounts for occlusion. A visual contour perception model was developed to reconstruct the contours of occluded rocks under natural stacking conditions，extracting their characteristic parameters. Considering the uncertainty in stacking angles，the three-dimensional particle sizes were estimated based on the random sampling of particle shapes and stacking angles，and the visual gradation on the surface layer was evaluated. To address discrepancies between visual and actual gradation caused by inter-layer occlusion，a mapping was constructed using the support vector regression（SVR） algorithm，enabling accurate inference of actual gradation while accounting for occlusion. Field experiments were conducted based on a certain hydropower project，verifying the feasibility and effectiveness of the proposed gradation inference method. The developed software and hardware system was deployed for on-site gradation detection，demonstrating results highly consistent with those obtained from the traditional sieving method. Compared to the conventional method，the proposed system provides significant advantages，including minimal interference，non-contact operation capability，and single-test completion within 1 minute. non-contact operation，and a less than 1 minute detection time per measurement. Furthermore，the testing frequency for transition materials and upstream rockfill was increased by 75 times and 250 times respectively. This system enables largescale，high-efficiency，and high-precision gradation of rock materials before placement on the dam. |
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