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Intelligent Reconstruction and Assembling of Pipeline from Point Cloud Data in Smart Plant 3D

机译:智能植物3D点云数据管道智能重建与组装

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The laser-scanned data of subsisting industrial pipeline plants are not only astronomically immense, but are withal intricately entwined like a net. The users must identify 3D points corresponding to each pipeline to be modelled in immensely colossal laser-scanned data sets. To accurately identify the 3D points corresponding to each pipeline, the users need to have some cognizance of direction and design of the pipelines. In addition, manually identifying each pipeline from gigantic and intricate scanned data is proximately infeasible, time-consuming and cumbersome process. In order to simplify and make the process more facile for reconstruction process an intelligent way of reconstruction and assembling of pipeline from point cloud data in Smart Plant 3D (SP3D) is proposed. The presented results shows that the proposed method indeed contribute automation of 3D pipeline model.
机译:最激光扫描的工业管道植物的数据不仅是天文学上的巨大,而且像网一样复杂缠绕。用户必须识别与每个管道对应的3D点以在巨大的巨大激光扫描数据集中建模。为了准确地识别对应于每个管道的3D点,用户需要对管道的方向和设计进行一些认识。此外,手动识别来自巨大和复杂的扫描数据的每个管道既有不可行,耗时,繁琐的过程。为了简化和使过程更加容易进行重建过程,提出了一种从智能工厂3D(SP3D)中的点云数据的智能重建和分配管道的智能方式。所提出的结果表明,该方法确实有助于3D管道模型的自动化。

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