Scan-to-BIM 자동화 기술을 활용한 건축물 단위의 BIM 모델 생성

• 영문명: BIM Model Generation at Building Level using Automated Scan-to- BIM Process: Focused on Demonstration of BIM Modeling for Gangwon Fire Service Academy
• 발행기관: 한국BIM학회
• 저자명: 박준우(Park, Jun-Woo) 김재홍(Kim, Jae-Hong) 김소현(Kim, So-Hyun) 이지민(Lee, Ji-Min) 최창순(Choi, Chang-Soon) 정광복(Jeong, Kwang-Bok) 이재욱(Lee, Jae-Wook)
• 간행물 정보: 『KIBIM Magazine』11권 4호, 53~62쪽, 전체 10쪽
• 주제분류: 공학 > 건축공학
• 파일형태: PDF
• 발행일자: 2021.12.30

영문 초록

The successful implementation of Scan-to-BIM automation depends on the entire process from scanning of buildings, including indoor facilities and furniture, to generating BIM models. However, the conventional Scan-to-BIM process requires a lot of time, manpower, and cost for the manual generation of BIM models including indoor objects. To solve this problem, this study applied a Scanto- BIM automation process using a deep learning model and parametric algorithm to an existing building, Kangwon Fire Service Academy. To improve the accuracy of the BIM model, after object data was extracted from the scan data, the data was corrected according to actual object-specific conditions. As a result, the accuracy of the BIM model created by the proposed Scan-to-BIM automation process was 91% compared to the actual area of the construction drawings. In addition, it was confirmed that the BIM objects were automatically generated for 10 object classes.

목차

1. 서론

2. Scan-to-BIM 자동화 방법

3. 3차원 데이터 기반 객체정보 추출

4. Parametric algorithm 적용

5. 실증 결과

6. 결론

감사의 글

References

키워드

Scan-to-BIM 자동화 딥러닝 파라메트릭 알고리즘 다이나모 공간관계 Scan-to-BIM Automation Deep Learning Parametric Algorithm Dynamo Spatial Relationship