Author:
Wang Xiang,Li Yang,Zhou Ziqi,Lv Xueyuan,Yuan Philip F.,Chen Lei
Abstract
AbstractConventional measuring techniques and equipment such as the level and total-station are commonly used in on-site construction to measure the position of building elements. However, a motion capture system can measure the dynamic 3D movements of markers attached to any target structure with high accuracy and high sampling rate. Considering the characteristics of prefabricated structures that is composed by lot of discrete building elements, advanced requirements for the on-site assembly monitoring is required. This paper introduces an innovative real-time monitoring technique for the DfD-based (Design for Disassembly) structure with the application of motion capture system and other hardware in an IoT-based BIM system. The design and construction method of the structure system, on-site setup of monitoring system and hardware, data acquisition and analysis method, calibration algorithm as well as the BIM system are further illustrated in the paper. The proposed method is finally applied in a real building project that is composed by thousand discrete building elements and covers a large area of 50*25 m. As demonstrator, such monitoring system is applied in the real construction of a DfD-based prefabricated steel structure in the “Water Cube” (Chinese National Aquatics Centre) in Beijing. The building process is successfully recorded and displayed on-site with the digital twin model in the BIM system. The construction states of the building elements are gathered with different kind of IoT techniques such as the RfID chips and QR-Codes. With the demand to control the flatness tolerance within 6 mm (within a 25*50 m area), a large area monitoring system was applied in the project and finally reduced the construction time within 20 days. The final tolerance is verified and further discussed2.
Publisher
Springer Nature Singapore
Reference6 articles.
1. Guy B, Ciarimboli N (2003) Design for disassembly in the built environment. WA, Resource Venture, Inc. Pennsylvania State University, City of Seattle
2. Bailey B, Wolf A (2007) Real time 3D motion tracking for interactive computer simulations, vol 3. Imperial College, London, UK
3. Hinrichs RN, McLean SP (1995) NLT and extrapolated DLT: 3-D cinematography alternatives for enlarging the volume of calibration. J Biomech 28(10):1219–1223
4. Aurand AM, Dufour JS, Marras WS (2017) Accuracy map of an optical motion capture system with 42 or 21 cameras in a large measurement volume. J Biomech 58:237–240
5. Raghu SL, Kang C-k, Whitehead P, Takeyama A, Conners R (2019) Static accuracy analysis of Vicon T40s motion capture cameras arranged externally for motion capture in constrained aquatic environments. J Biomech 89:139–42