Enhancing extraction of two-dimensional engineering drawings from three-dimensional data of existing buildings

Abstract

Accurately extracting two-dimensional (2D) engineering drawings from existing buildings' three-dimensional (3D) data is crucial for building renovation, protection, and research. This research aims to optimize existing algorithms and propose new ones to achieve fast, automatic, accurate, and rich-information extraction of 2D engineering drawings. The study focuses on 2D orthographic drawings, the curvature analysis of 3D models, the conversion from point grids to polylines, and the automated dimensioning of drawings. Novel methods are utilized to analyze 3D data based on obtained point cloud and mesh models. In our experiments, each model required four days of fieldwork and ten days of data processing. The automated approach generated accurate 2D curve drawings, significantly more efficient than manual drawing in Autocad software. The dimensioning work, typically taking hours, was completed in just 2 min using a computer algorithm. The critical contribution of this study lies in providing essential theoretical and practical guidance for promoting the development of digital building technology and engineering practice. This research introduces optimized algorithms and novel methods for extracting 2D engineering drawings from 3D data, addressing the challenges of accuracy, efficiency, and information richness. The efficiency gains achieved and the integration of automation highlight the novelty of this research.