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Challenges of Identifying Steel Sections for the Generation of As-Is BIMs from Laser Scan Data

机译:从激光扫描数据中识别钢部分的钢结构的挑战

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Purpose When a laser scan is performed and no prior information is available about the building, standard sections of components need to be identified from point cloud data in order to generate informative as-is building information models (BIMs). Currently, the standard steel sections used at a site are not automatically identified from the point cloud data. Various issues related to the laser scan data, challenge automation, such as occlusions, missing data points, angle of incidence, and imprecision of measurements on the data. Method: The research described in this paper relates to the manual determination of steel beam sizes used in a steel worker training facility, which contained about 16 beams, 63 columns, and 12 scans collected over 4 days of construction. Results & Discussion we identified that occlusions and noise are the major challenges associated with recording accurate dimension measurements. The identification of correct steel sections based on such inaccurate measurements is even more challenging since the decision should be based on all defining (e.g., flange width, depth) dimensions.
机译:目的当进行激光扫描,并没有事先信息可关于建筑物,组分的标准部分需要从点云数据,以便生成信息作为-是建筑信息模型(BIMS)标识。目前,在现场使用的标准钢型材不会自动从点云数据识别。与激光扫描数据的各种问题,挑战自动化,如阻塞,丢失的数据点,入射角度,以及对数据测量不准确。方法:在此论文中描述的研究涉及的手动确定在钢铁工人训练设施,其中含有约16个波束,63列,并且收集结构4天12次扫描中使用钢梁尺寸。结果和讨论我们确定了遮挡和噪声与记录准确的尺寸测量有关的重大挑战。基于这样的测量不准确正确型钢的识别更加具有挑战性,因为决定应当基于所有定义(例如,凸缘宽度,深度)的尺寸。

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