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

  • Holi, Pavitra; 
  • Park, Seong Sill; 
  • Patil, Ashok Kumar; 
  • Kumar, G. Ajay; 
  • Chai, Young Ho
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SCOPUS

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초록

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.

키워드

Point cloud; Segmentation; Cylinder detection; SP3D automation
제목
Intelligent Reconstruction and Assembling of Pipeline from Point Cloud Data in Smart Plant 3D
저자
Holi, Pavitra; Park, Seong Sill; Patil, Ashok Kumar; Kumar, G. Ajay; Chai, Young Ho
DOI
10.1007/978-3-319-24078-7_36
발행일
2015-09
유형
Proceedings Paper
저널명
Lecture Notes in Computer Science
권
9315
페이지
360 ~ 370