As buildings become increasingly complex, construction monitoring using various sensors is urgently needed for both more systematic and accurate safety management and high-quality productivity in construction. In this study, a monitoring system that is composed of a laser displacement sensor (LDS) and a wireless sensor node was proposed and applied to an irregular building under construction. The subject building consists of large cross-sectional members, such as mega-columns, mega-trusses, and edge truss, which secured the large spaces. The mega-trusses and edge truss that support this large space are of the cantilever type. The vertical displacement occurring at the free end of these members was directly measured using an LDS. To validate the accuracy and reliability of the deflection data measured from the LDS, a total station was also employed as a sensor for comparison with the LDS. In addition, the numerical simulation result was compared with the deflection obtained from the LDS and total station. Based on these investigations, the proposed wireless displacement monitoring system was able to improve the construction quality by monitoring the real-time behavior of the structure, and the applicability of the proposed system to buildings under construction for the evaluation of structural safety was confirmed.
References
[1]
Hegger, J. High-strength concrete for a 186 m high office building in Frankfurt, Germany. Eng. Struct. 1996, 11, 850–854.
[2]
Tatsuya, W.; Noriyuki, F.; Yasuo, I.; Takashi, S. Automated construction system for high-rise reinforced concrete buildings. Autom. Constr. 2000, 9, 229–250.
[3]
Abid, A.; Ribakov, Y. Recent trends in steel fibered high-strength concrete. Mater. Des. 2011, 32, 4122–4151.
[4]
Ikeda, Y.; Harada, T. Application of the Automated Building Construction System Using the Conventional Construction Method Together. Proceedings of the 23rd International Symposium on Automation and Robotics in Construction, Tokyo, Japan, 3–5 October 2006.
[5]
Hu, Z.; Zhang, J. BIM- and 4D-based integrated solution of analysis and management for conflicts and structural safety problems during construction: 2. Development and site trials. Autom. Constr. 2011, 20, 167–180.
[6]
Zhou, W.; Whyte, J.; Sacks, R. Construction safety and digital design: A review. Autom. Constr. 2012, 22, 102–111.
[7]
Zhang, S.; Teizer, J.; Lee, J.; Charles, M.E.; Manu, V. Building Information Modeling (BIM) and safety. Automatic safety checking of construction models and schedules. Autom. Constr. 2012, 29, 183–195.
[8]
Park, H.S.; Lee, H.M.; Adeli, H.; Lee, I. A new approach for health monitoring of structures: Terrestrial laser scanning. Comput. Aided Civil Infrastr. Eng. 2007, 22, 19–30.
[9]
Lee, H.M.; Park, H.S. Estimation of deformed shape of beam structure using 3D coordinate information from terrestrial laser scanning. Comput. Model. Eng. Sci. 2008, 29, 29–44.
[10]
Ni, Y.Q.; Li, B.; Lam, K.H.; Zhu, D.; Wang, Y.; Lynch, J.P.; Law, K.H. In-construction vibration monitoring of a super-tall structure using a long-range wireless sensing system. Smart Struct. Syst. 2010, 7, 83–102.
[11]
Wu, Z.F.; Gao, F. Application and research of steel structure construction monitoring of costa rica state stadium canopy with measurement robot. Energy Procedia 2011, 13, 2794–2801.
[12]
Xia, Y.; Ni, Y.Q.; Zhang, P.; Liao, W.Y.; Ko, J.M. Stress development of a supertall structure during construction: Field monitoring and numerical analysis. Comput. Aided Civil Infrastr. Eng. 2011, 26, 1–8.
[13]
Salawu, O.S. Detection of structural damage through changes in frequency: A review. Eng. Struct. 1997, 19, 718–723.
[14]
Doebling, S.W.; Farrar, C.R.; Prime, M.B.; Shevitz, D.W. Damage Identification and Health Monitoring of Structural and Mechanical Systems from Change in Their Vibration Characteristics: A Literature Review. Technical Report No. LA-13070-MS; Los Alamos National Laboratory: Los Alamos, NM, USA, 1996.
[15]
Carden, E.P.; Fanning, P. Vibration based condition monitoring. A review. Struct. Health Monit. 2004, 3, 355–377.
Coutts, D.R.; Wang, J.; Cai, J.G. Monitoring and analysis of results for two strutted deep excavations using vibrating wire strain gauges. Tunn. Underground Space Technol. 2001, 16, 87–92.
[18]
Park, H.S.; Jung, H.S.; Kwon, Y.H.; Seo, J.H. Mathematical models for assessment of the safety of steel beams based on average strains from long gage optic sensors. Sens. Actuators A Phys. 2005, 125, 109–113.
[19]
Park, H.S.; Jung, S.M.; Lee, H.M.; Kwon, Y.H.; Seo, J.H. Analytical models for assessment of the safety of multi-span steel beams based on average strains from long gage optic sensors. Sens. Actuators A Phys. 2007, 137, 6–12.
[20]
Lee, H.M.; Park, H.S. Measurement of maximum strain of steel beam structures based on average strains from vibrating wire strain gages. Exp. Technol. 2013, 37, 23–29.
[21]
Nakamura, S. GPS measurement of wind-induced suspension bridge girder displacements. J. Struct. Eng. 2000, 126, 1413–1419.
[22]
Celebi, M.; Eeri, M.; Sanli, A. GPS in pioneering dynamic monitoring of long-period structures. Earthq. Spcetra 2002, 18, 47–61.
[23]
Tamurra, Y.; Matsui, M.; Pagnini, L.C.; Ishibashi, R.; Yoshida, A. Measurement of wind-induced response of building using RTK-GPS. J. Wind Eng. Ind. Aerodyn. 2002, 90, 1783–1793.
[24]
Park, H.S.; Sohn, H.G.; Kim, I.S.; Park, J.H. Application of GPS to monitoring of wind-induced responses of high-rise buildings. Struct. Des. Tall Spec. Build. 2007, 17, 117–132.
[25]
Breuer, P.; Chmielewski, T.; Gorski, P.; Konopka, E. Application of GPS technology to measurement of displacement of high-rise structures due to weak winds. J. Wind Eng. Ind. Aerodyn. 2002, 90, 223–230.
[26]
Fraser, C.S.; Riedel, B. Monitoring the thermal deformation of steel beams via vision metrology. J. Photogramm. Remote Sens. 2000, 55, 268–276.
[27]
Lee, J.-J.; Shinozuka, M. A vision-based system for remote sensing of bridge displacement. NDT E Int. 2006, 39, 425–431.
[28]
Nassif, H.H.; Gindy, M.; Davis, J. Comparison of laser doppler vibrometer with contact sensors for monitoring bridge deflection and vibration. NDT E Int. 2005, 38, 213–218.
[29]
Balendra, T.; Anwar, M.P.; Tey, K.L. Direct measurement of wind-induced displacement in tall building models using laser positioning technique. J. Wind Eng. Ind. Aerodyn. 2005, 93, 399–412.
[30]
Xu, Y.L.; Zhang, J.; Li, J.C.; Xia, Y. Experimental investigation on statistical moment-based structural damage detection method. Struct. Health Monit. 2009, 8, 555–571.
[31]
Xu, B.; Song, G.; Masri, S.F. Damage detection for a frame structure model using vibration displacement measurement. Struct. Health Monit. 2012, 11, 281–192.
[32]
Lynch, J.P.; Loh, K.J. A summary review of wireless sensors and sensor networks for structural health monitoring. Shock Vib. Dig. 2006, 38, 91–128.
[33]
Shieh, J.; Huber, J.E.; Fleck, N.A.; Ashby, M.F. The selection of sensors. Prog. Mater. Sci. 2001, 46, 461–504.
[34]
Zhang, F.; Qu, X.; Ouyang, J. An automated inner dimensional measurement system based on a laser displacement sensor for long-stepped pipes. Sensors 2012, 12, 5824–5834.
[35]
Keyence Global Home. Available online: http://www.keyence.com/ (accessed on 2 May 2013).
[36]
Viterbi, A.J. CDMA: Principles of Spread Spectrum Communication; Addison-Wesley: Reading, MA, USA, 1995.
[37]
Lee, H.M.; Kim, J.M.; Sho, K.; Park, H.S. A wireless vibrating wire sensor node for continuous structural health monitoring. Smart Mater. Struct. 2010, doi:10.1088/0964-1726/19/5/055004.
[38]
Midas User Support System. Available online: http://en.midasuser.com/ (accessed on 2 May 2013).
[39]
Casciati, F.; Domaneschi, M.; Faravelli, L. Design and implementation of a pointer system controller. Nonlinear Dyn. 2004, 36, 203–215.
