A Semi-Automatic Approach to Detect Structural Components from CAD Drawings for Constructing As-Is BIM Objects

Abstract

With the increasing implementation of building information model (BIM) in operations and maintenance (O&M) management for existing buildings, various new data detection technologies for constructing an as-is BIM have been proposed and developed in past decades. In particular, extracting information from existing CAD documents is still a significant research area in the as-is BIM construction process. Data saved in CAD formats are unstructured and consequently it is hard to extract information and recognize objects in a systematic approach. With the ultimate goal of developing an effective and applicable approach to assist constructing as-is BIM objects, a novel semi-automatic approach is developed to detect structural components from CAD drawings. This approach mainly consists of a data processing part and a data management part. The data processing part defines the location of a structural component through recognizing special symbols in a floor plan and then extracting data from the floor plan using the optical character recognition (OCR) algorithm. The data management part analyzes and takes meaningful information from the extracted data based on predefined outlines. This paper first summarizes state-of-the-art information detection and analysis methods from CAD drawings. Then, the methodology and the prototype application developed in Matlab are introduced and discussed. Moreover, a preliminary set of tests using an office building and the analysis results from the tests are discussed as a case study from the perspectives of applicability and accuracy. Lastly, future works and limitations are also addressed.