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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件的钢结构的挑战

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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,当执行激光扫描并且没有现有信息的建筑物中,需要从点云数据中识别组件的标准部分,以便生成信息的信息模型(BIMS)。目前,站点上使用的标准钢部分不会自动从点云数据中识别。与激光扫描数据有关的各种问题,挑战自动化,例如闭塞,缺少数据点,入射角,数据对数据的测量不义。方法:本文描述的研究涉及一种手动确定钢铁梁尺寸的钢梁尺寸,其包含大约16个梁,63个柱,12天的施工超过4天。结果与讨论,我们确定了遮挡和噪声是与记录精确尺寸测量相关的主要挑战。基于这种不准确的测量的正确钢部分的识别是更具挑战性,因为该决定应基于所有定义(例如法兰宽度,深度)尺寸。

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