CUED Publications database

Modelling, management, and visualisation of structural performance monitoring data on BIM

Delgado, JMD and Brilakis, I and Middleton, C (2016) Modelling, management, and visualisation of structural performance monitoring data on BIM. In: UNSPECIFIED pp. 543-549..

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Abstract

© The authors and ICE Publishing: All rights reserved, 2016. The use of systems to monitor the condition and structural performance of buiIt-Assets is becoming common practice. The data acquired by these systems could lead to reductions in construction, operational, and maintenance costs and improved performance and quality by enabling informed decision making. Nevertheless, the data as outputted by the systems is of little use and value. First, it needs to be processed and put into geometric context within the built-Asset, which simplifies the interpretation and analysis of the data. This supports informed decision making that leads to effective actions. This paper presents an overview of an approach to model structural performance monitoring systems and to include and visualise sensor data on BIM models in a manner that facilitates decision making. This paper addresses aspects related to (1) interoperability and standards for data modelling; (2) processing and management of sensor data on BIM models; and (3) visualisation of sensor data directly on the BIM model. A precast concrete bridge, in Staffordshire, UK, has been used as case study. It has been installed with two types of fibre optic systems to monitor the manufacturing process of its pre-stressed beams. The paper shows that BEM provisions to support structural performance monitoring tasks are not sufficient yet. It also showcases that by including and visualising monitoring data directly on BIM models it gains geometrical context within the built asset. This facilitates its analysis and increases its value.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Subjects: UNSPECIFIED
Divisions: Div D > Construction Engineering
Depositing User: Cron Job
Date Deposited: 17 Jul 2017 19:37
Last Modified: 24 Aug 2017 01:28
DOI: