Towards a digital twin of a storage tank using laser scan data

L. Truong-Hong*, N. Nguyen, R. Lindenbergh, P. Fisk, T. Huynh

*Corresponding author for this work

Research output: Contribution to journalConference articleScientificpeer-review

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Abstract

This paper proposes a methodology to automatically extract components of an oil storage tank from terrestrial laser scanning (TLS) point clouds, and subsequently to create a three-dimensional (3D) solid model of the tank for numerical simulation. The proposed method is integrated into a smart analysis layer of a digital twin platform consisting of three main layers: (1) smart analysis, (2) data storage, and (3) visualisation and user interaction. In this proposed method, primary components of the tank were automatically extracted in a consecutive order from a shell wall to roof and floor. Voxel-based RANSAC is employed to extract voxels containing point clouds of the shell wall, while a valley-peak-valley pattern based on kernel density estimation is implemented to remove outlier points within voxels representing to the shell wall and re-extract data points within voxels adjoined to the shell wall. Moreover, octree-based region growing is employed to extract a roof and floor from remaining point clouds. An experimental showed that the proposed framework successfully extracted all primary components of the tank and created a 3D solid model of the tank automatically. Resulting point clouds of the shell wall were directly used for estimating deformation and a 3D solid model was imported into finite element analysis (FEA) software to assess the tank in terms of stress-strain. The demonstration shows that TLS point clouds can play an important role in developing the digital twin of the oil storage tank.

Original languageEnglish
Pages (from-to)119-124
Number of pages6
JournalInternational Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
Volume46
Issue number4/W4-2021
DOIs
Publication statusPublished - 2021
Event16th 3D GeoInfo Conference 2021 - New York City, United States
Duration: 11 Oct 202114 Oct 2021

Keywords

  • Deformation
  • Digital twin
  • Finite element analysis
  • Point clouds
  • Segmentation
  • Storage tank

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