A semi-automatic approach to detect structural components from cad drawings for constructing As-Is bim objects

Qiuchen Lu, Sanghoon Lee

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

15 Scopus citations

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.

Original languageEnglish
Title of host publicationComputing in Civil Engineering 2017
Subtitle of host publicationInformation Modeling and Data Analytics - Selected Papers from the ASCE International Workshop on Computing in Civil Engineering 2017
EditorsKen-Yu Lin, Ken-Yu Lin, Nora El-Gohary, Nora El-Gohary, Pingbo Tang, Pingbo Tang
PublisherAmerican Society of Civil Engineers (ASCE)
Pages84-91
Number of pages8
ISBN (Electronic)9780784480823, 9780784480847
ISBN (Print)9780784480823
DOIs
StatePublished - 2017
Event2017 ASCE International Workshop on Computing in Civil Engineering, IWCCE 2017 - Seattle, United States
Duration: 25 Jun 201727 Jun 2017

Publication series

NameCongress on Computing in Civil Engineering, Proceedings

Conference

Conference2017 ASCE International Workshop on Computing in Civil Engineering, IWCCE 2017
Country/TerritoryUnited States
CitySeattle
Period25/06/1727/06/17

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