Research on automatic visualization technology of bridge disease information based on BIM

Liangtao Nie; Guojiao Hou; Weimin Li; Pengfei Li

doi:10.1117/12.2627935

14 March 2022 Research on automatic visualization technology of bridge disease information based on BIM

Liangtao Nie, Guojiao Hou, Weimin Li, Pengfei Li

Proceedings Volume 12165, International Conference on Intelligent Traffic Systems and Smart City (ITSSC 2021); 1216505 (2022) https://doi.org/10.1117/12.2627935
Event: 2021 International Conference on Intelligent Traffic Systems and Smart City, 2021, Zhengzhou, China

Abstract

The problems of unintuitive expression of bridge inspection disease information and difficult query of historical disease records are widespread. To solve the above problems, this paper proposes an automatic three-dimensional (3D) visualization expression method of bridge inspection disease information based on BIM (Building Information Modeling) technology. The construction technology of bridge BIM model based on completed drawings is studied. The storage structure of bridge disease information database is designed and the disease information is stored in a time-sharing classification manner. Studying the 3D expression method of common diseases and the conversion relationship model of bridge global coordinates and component local coordinates, the automatic matching and visual expression of disease information and 3D model of bridge are realized. The research results can provide intuitive and visual information query means for bridge maintenance and operation, and help to improve the efficiency of information utilization and rapid formulation of maintenance schemes.

Citation Download Citation

Liangtao Nie, Guojiao Hou, Weimin Li, and Pengfei Li "Research on automatic visualization technology of bridge disease information based on BIM", Proc. SPIE 12165, International Conference on Intelligent Traffic Systems and Smart City (ITSSC 2021), 1216505 (14 March 2022); https://doi.org/10.1117/12.2627935

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available