Automatic 3D CAD models reconstruction from 2D orthographic drawings

Zhang, Chao; Pinquié, Romain; Polette, Arnaud; Carasi, Gregorio; Charnace, Henri De; Pernot, Jean-Philippe

doi:10.1016/j.cag.2023.05.021

Cited by 9 publications

(2 citation statements)

References 21 publications

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“…Similarly, Lu et al [48] reconstruct the model component by component by modelling each component solid individually according to their shape coordinates and 3D attributes. Zhang, C. et al [70] developed a pattern-matching technique capable of reconstructing 3D CAD solid models from 2D orthographic drawings, effectively capturing the complex curvature of solid objects. While initially applied to individual solid objects, their methodology shows promise for broader implementation across entire buildings, addressing the challenges encountered by previous methods when dealing with curved geometries.…”

Section: Three-dimensional Modellingmentioning

confidence: 99%

Automatic Reconstruction of 3D Models from 2D Drawings: A State-of-the-Art Review

Feist,

Jacques de Sousa,

Sanhudo

et al. 2024

Eng

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Among the methods of 3D reconstruction, the automatic generation of 3D models from building documentation is one of the most accessible and inexpensive. For 30 years, researchers have proposed multiple methods to automatically generate 3D models from 2D drawings. This study compiles this research and discusses the different methods used to generate 3D models from 2D drawings. It offers a critical review of these methods, focusing on the coverage and completeness of the reconstruction process. This review allows us to identify the research gaps in the literature, and opportunities for improvement are identified for future research.

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Section: Three-dimensional Modellingmentioning

confidence: 99%

Automatic Reconstruction of 3D Models from 2D Drawings: A State-of-the-Art Review

Feist,

Jacques de Sousa,

Sanhudo

et al. 2024

Eng

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“…Hou et al [57] proposed a GCN-based FuS-GCN approach as a 3D model classification and search method for application to boundary representation 3D CAD when operating in a mesh or point cloud. Zhang et al [58] suggested an approach for generating a 3D CAD model from an isometric projection image. Their approach was verified in an open dataset composed of thousands of 3D shapes, and it achieved an F-score of 99.59%.…”

Section: Three-dimensional Modeling Layout For Plant Projectmentioning

confidence: 99%

Auto-Routing Systems (ARSs) with 3D Piping for Sustainable Plant Projects Based on Artificial Intelligence (AI) and Digitalization of 2D Drawings and Specifications

Kang,

Choi,

Lee

et al. 2024

Sustainability

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The engineering sector is undergoing digital transformation (DT) alongside shifts in labor patterns. This study concentrates on piping design within plant engineering, aiming to develop a system for optimal piping route design using artificial intelligence (AI) technology. The objective is to overcome limitations related to time and costs in traditional manual piping design processes. The ultimate aim is to contribute to the digitalization of engineering processes and improve project performance. Initially, digital image processing was utilized to digitize piping and instrument diagram (P&ID) data and establish a line topology set (LTS). Subsequently, three-dimensional (3D) modeling digital tools were employed to create a user-friendly system environment that visually represents piping information. Dijkstra’s algorithm was implemented to determine the optimal piping route, considering various priorities during the design process. Finally, an interference avoidance algorithm was used to prevent clashes among piping, equipment, and structures. Hence, an auto-routing system (ARS), equipped with a logical algorithm and 3D environment for optimal piping design, was developed. To evaluate the effectiveness of the proposed model, a comparison was made between the bill of materials (BoM) from Company D’s chemical plant project and the BoM extracted from the ARS. The performance evaluation revealed that the accuracy in matching pipe weight and length was 105.7% and 84.9%, respectively. Additionally, the accuracy in matching the weight and quantity of fittings was found to be 99.7% and 83.9%, respectively. These findings indicate that current digitalized design technology does not ensure 100% accurate designs. Nevertheless, the results can still serve as a valuable reference for attaining optimal piping design. This study’s outcomes are anticipated to enhance work efficiency through DT in the engineering piping design sector and contribute to the sustainable growth of companies.

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Shape functions to scanner comparison

Pajerová,

Koptiš

2024

Int J Adv Manuf Technol

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In the optical scanning, the processed data are in the form of point clouds that can be organised into the triangular meshes and can represent the surface with the given inaccuracy of the scanner. Meshes of special surfaces (such as sphere or ball bar) are used for the scanner calibration, qualification and verification. These artefacts restrict the calibration process, because their sizes must be periodically calibrated by the relevant institutions.The aim of this paper is to present new possibilities for optical laser scanner accuracy comparison. Three types of laser scanners with different accuracies were used. The calibration sphere was used to compare the results of the deviations (the commonly used method for scanner accuracy verification) from calibrated value with the results of new methods that use shape functions measuring distances, cone heights or curvatures. The measurement system analysis was used to verify that these functions can be used for scanners comparison. The comparison of shape distributions obtained from results of shape functions in the form of polylines was used to compare scanners according to their accuracies. The comparison of shape distribution results was done using ranges and Minkowski $${L}_{1}$$ L 1 norm.

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Automatic 3D CAD models reconstruction from 2D orthographic drawings

Cited by 9 publications

References 21 publications

Automatic Reconstruction of 3D Models from 2D Drawings: A State-of-the-Art Review

Automatic Reconstruction of 3D Models from 2D Drawings: A State-of-the-Art Review

Auto-Routing Systems (ARSs) with 3D Piping for Sustainable Plant Projects Based on Artificial Intelligence (AI) and Digitalization of 2D Drawings and Specifications

Shape functions to scanner comparison

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