BIM-Based Data Management System for Structural Health Monitoring

Pang, Ding Kang (2020) BIM-Based Data Management System for Structural Health Monitoring. Final Year Project, UTAR.

Preview

PDF Download (3713Kb) | Preview

Abstract

Structural Health Monitoring (SHM) is important to identify and quantify the damage or deterioration state of a structure that might occur over the service life. However, SHM involves enormous volume of raw data in real-time and the analysis and interpretation of the data is a challenging issue. Current SHM practices are limited due to the limitation of storing and retrieving data. Besides, SHM practices also lack of visualisation where processed data are displayed as images and graphs only. In the recent years, Building Information Modeling (BIM) is gaining popularity due to its abundant benefits. In this study, a research framework for integrating a BIM-based data management system into SHM was developed. The objectives of the study are to investigate traditional SHM and how BIM can be incorporated into it, to review the current BIM-based data management system and to investigate the suitability of the proposed BIMbased data management system for the SHM. A proposed was carried out using the BIM related software and visual programming platform Revit® 2021 by Autodesk and Dynamo. In this study, a 3D model of a four-story concrete model was constructed together with the SHM system in Revit. Then, five visual programming modules for linking SHM to BIM are constructed with Dynamo to automatically extract and manage processed data. The data and information of the structural elements are stored in Revit model to reduce the risk of data loss throughout the lifecycle of the project. Besides, the BIM-based SHM enable damage visualisation via colour-coding the damaged elements in the 3D model. The study proposed the framework for BIM-based SHM that enable real-time data storage, visualisation of the damaged elements, and manage real-time data within its dynamic BIM model, where both data and analysis can be viewed on the same platform.

Actions (login required)