Shi, Xin, Liu, Yu-shen, Gao, Ge, Gu, Ming and Li, Haijiang ORCID: https://orcid.org/0000-0001-6326-8133 2018. IFCdiff: A content-based automatic comparison approach for IFC files. Automation in Construction 86 , pp. 53-68. 10.1016/j.autcon.2017.10.013 |
Preview |
PDF
- Accepted Post-Print Version
Available under License Creative Commons Attribution Non-commercial No Derivatives. Download (1MB) | Preview |
Abstract
As the usage of IFC (Industry Foundation Classes) files in construction industry is on the dramatic increase, it often requires effective IFC comparison methods to keep track of important changes occurring during the lifecycle of construction projects. However, most IFC comparisons are based on a visual inspection, a manual count and a check of selective attributes. Although a few techniques about automatic IFC comparisons have been developed recently, they are usually very time-consuming, and are sensitive to the GUID change or redundant instances in IFC files. To address these issues, this paper presents a content-based automatic comparison approach, named IFCdiff, for detecting differences between two IFC files. This approach starts with a comprehensive analysis of the structure and content of each IFC file, and then constructs its hierarchical structure along with eliminating redundant instances. Next, the two hierarchical structures are compared with an iterative bottom-up procedure instead of the original files. The presented approach fully takes into account the content of IFC files fully without the need of flattening instances in IFC files. In contrast with previous methods, our approach can greatly reduce the computational time and space, and the comparison result is not sensitive to re-dundant instances in IFC files. Finally, we demonstrate a potential application to incremental backup of IFC files. The software can be found at: http://cgcad.thss.tsinghua.edu.cn/liuyushen/ifcdiff/.
Item Type: | Article |
---|---|
Date Type: | Publication |
Status: | Published |
Schools: | Engineering |
Publisher: | Elsevier |
ISSN: | 0926-5805 |
Date of First Compliant Deposit: | 10 November 2017 |
Date of Acceptance: | 17 October 2017 |
Last Modified: | 08 Nov 2023 02:21 |
URI: | https://orca.cardiff.ac.uk/id/eprint/106396 |
Citation Data
Cited 24 times in Scopus. View in Scopus. Powered By Scopus® Data
Actions (repository staff only)
Edit Item |