基于无人机技术的沥青厂集料堆体积测算方法

    Method for Volume Measurement and Calculation of Asphalt Aggregate Based on UAV Technology

    • 摘要: 集料是生产沥青混合料的重要原材料之一,其库存量体积计算效率与精度对集料智能化管理具有重要意义. 针对传统人工盘点集料体积方法存在效率低、精度差等问题,应用无人机倾斜摄影测量技术进行集料体积的自动化计算研究. 以北京市政路桥建材集团怀柔沥青厂室外仓库集料为研究对象,应用大疆“御”Pro行器、Agisoft Metashape软件,基于无人机倾斜摄影测量技术采集集料影像,基于运动恢复结构算法建立集料稀疏点云,基于多视角立体算法生成密集点云,基于表面重建算法、纹理映射算法生成具有表面纹理的三维模型,实现沥青集料的可视化管理,基于生成的集料点云研究基于三角网法的集料体积计算方法. 结果表明,采用无人机倾斜摄影技术能够快速获取室外仓库集料影像,提高集料体积计算效率,精度相对于传统方法较高,满足工程需要. 模型参数设置对最终结果无显著影响,但模型参数设置为最高时会造成建模时间显著增加,因此模型参数设置为最低时,将会大大节省时间、提高建模效率,在实际应用中具有重要意义. 研究为集料可视化管理、智能化管理提供技术支撑,具有较强的工程实用价值.

       

      Abstract: Aggregate is an important raw material in the production of asphalt, and its inventory volume calculation efficiency and accuracy are important for aggregate intelligent management. Aiming at the problems of low efficiency and poor accuracy in traditional manual counting of aggregate volume, the unmanned aerial vehicle (UAV) tilt photogrammetry technology was used to carry out automated calculation of aggregate volume. Taking the aggregates from the outdoor warehouse of the Huairou Asphalt Plant of Beijing Municipal Road and Bridge Building Materials Group as a research object, using DJI Pro aircraft and Agisoft Metashape software, the data was collected based on the UAV tilt photogrammetry technology. The point cloud model was generated based on the structure from motion algorithm and the multi-view stereo algorithm. A three-dimensional model was established with surface texture based on surface reconstruction algorithm and texture mapping algorithm, realized the visual management of asphalt aggregate, and based on the generated aggregate point cloud, the calculation method of aggregate volume based on triangulation method was studied. Results show that the UAV tilt photography technology quickly obtains the aggregate image of outdoor warehouse, and improves the efficiency of aggregate volume calculation. The relative error between the volume calculation results and the aggregate storage data was controlled within 15%, which met the engineering need. The model parameter setting had no significant effect on the final result, but when the model parameter was set to the highest, the modeling time increased significantly. Therefore, when the model parameter was set to the lowest, it greatly saved time and improved the modeling efficiency, which was of great significance in practical application. The research provides technical support for visual management and intelligent management of aggregate, and has high engineering value.

       

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