Manhattan-World Assumption for As-Built Modeling Industrial Plant

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As industrial plants such as chemical and power plants continue to age, their CAD models are increasingly required for model-based planning and simulation. However, in the case of old plants, the original CAD models rarely exist, and hand-drawings do not precisely match the present states of the plants due to repeated remodeling. It is therefore becoming a common approach to reconstruct CAD models from the point cloud of such plants captured by terrestrial laser scanning and use these models for the above purposes. Such a reconstruction process is usually called “as-built modeling”. However, existing methods for as-built modeling come with such problems as the need for many human operations and computational cost. In this paper, we propose an automatic and efficient method for as-built modeling industrial plants using Manhattan-world assumption which states that there exist three dominant axes orthogonal to each other in artificial buildings and the internal parts are arranged so that they are parallel or orthogonal to one of them. In the case of industrial plants, it is reasonable to consider that long pipes and shaped steels are arranged so that they follow this assumption. In addition, plant parts are supposed to be designed as long linear sweep surfaces on CAD system or hand drawings. Our method can automatically recognize such sweep parts and their cross sectional shape which follow the assumption, as well as efficiently recognize them even from a large point cloud which may contain as many as one hundred million points in a few minutes. We demonstrate the effectiveness of our proposed method from various experiments on real scanned data.

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Periodical:

Key Engineering Materials (Volumes 523-524)

Edited by:

Tojiro Aoyama, Hideki Aoyama, Atsushi Matsubara, Hayato Yoshioka and Libo Zhou

Pages:

350-355

Citation:

T. Mizoguchi et al., "Manhattan-World Assumption for As-Built Modeling Industrial Plant", Key Engineering Materials, Vols. 523-524, pp. 350-355, 2012

Online since:

November 2012

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$38.00

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