Problems review of the health monitoring of tall type buildings

• Autorzy: Saidov K. , Szpytko J.

Identyfikatory

DOI

10.5604/12314005.1165438

• Języki publikacji: EN

Abstrakty

EN

Structural monitoring systems are widely adopted to monitor the behaviour of structures during forced vibration testing or natural excitation. Structural monitoring systems can be found in a number of common structures including aircrafts, ships, bridges, mechanical and civil structures. For example, some building design codes mandate that structures located in regions of high seismic activity have structural monitoring systems installed. This paper is focused on selected problems review of the health monitoring of tall type buildings and automation. The actual problem in structural health monitoring (SHM) is to find the structural damage and its location by performing some statistical pattern recognition on the measured data termed as feature extraction. The damage caused by environmental loads should be repaired; otherwise, it will expand with time and might lead to complete system failure. Dynamic parameters such as velocity, acceleration, and displacement play a significant role in determining the structure dynamics. As well as this paper highlights comprehensive survey about monitoring system used in civil structures (buildings) involving the issues such as influence of different outer forces on buildings and other critical methods for proper analysis of monitoring system used in tall type buildings. Additionally, wide-scale review related to an automation aspect of structural health monitoring of buildings has been presented. A significant observation from this review is that although there are many more SHM studies being reported, the investigators, in general, have not yet fully embraced the well-developed tools from statistical pattern recognition. As such, the discrimination procedures employed are often lacking the appropriate rigor necessary for this technology to evolve beyond demonstration problems carried out in laboratory setting.

Słowa kluczowe

EN

structural health monitoring (SHM); tall frame type buildings; automation

• Wydawca: Łukasiewicz Research Network - Institute of Aviation ; European Science Society of Powertrain and Transport KONES Poland ; Wydawnictwo Instytutu Technicznego Wojsk Lotniczych
• Czasopismo: Journal of KONES
• Rocznik: 2015
• Tom: Vol. 22, No. 2
• Strony: 191--204
• Opis fizyczny: Bibliogr. 60 poz., rys.

Twórcy

autor

Saidov K.

• AGH University of Science and Technology Faculty of Mechanical Engineering and Robotics A. Mickiewicza Avenue 30, 30-059 Krakow, Poland

autor

Szpytko J.

• AGH University of Science and Technology Faculty of Mechanical Engineering and Robotics A. Mickiewicza Avenue 30, 30-059 Krakow, Poland

Bibliografia

• [1] Abdelrazaq, S. E., The program in place at the Burj Khalifa tower serves as a model for new monitoring programs, http://cenews.com/article/9742/structural-vital-signs, 2014.
• [2] Andersen, E. Y., Pedersen, L., Structural monitoring of the Great Belt East Bridge, In: Krokebogr, J. (editor), Strait crossings, 94, pp. 189-95, Balkema, Rotterdam 1994.
• [3] Auweraer, H., Peeters, B., International research projects on structural health monitoring: an overview, Structural Health Monitoring, Vol. 2 (4), pp. 341-358, 2003.
• [4] Addario-Berry, L., Chor B., Hallett, M., Lagergren, J., Panconesi, A., Wareham, T., Ancestral maximum likelihood of evolutionary trees is hard, Journal of Algorithms in Bioinformatics, Vol. 2812, pp. 202-215, 2003.
• [5] Begg, R. D., Mackenezie, A. C., Dodds, C. J., Loland, O., Structural integrity monitoring using digital processing of vibration signals, Proceedings of the 8th Annual Offshore Technology Conference, pp. 305-311, Houston, TX 1976.
• [6] Bennett, K. P., Bredensteiner, E. J., Geometry in Learning, Geometry at Work; Edited by C, Gorini, Mathematical Association of America, 2000.
• [7] Brownjohn, J. M. W., Moyo, P., Omenzetter, P., Chakraborty, S., Lessons from monitoring the performance of highway bridges, Structures Control Health Monitoring, Vo. 12 (3-4), pp. 227-244, July 2005.
• [8] Boser, B. E., Guyon, I., Vapnik, V., A training algorithm for optimal margin classifiers, Fifth ACM Workshop on Computational Learning Theory (COLT), pp. 144–152, ACM Press, New York 1992.
• [9] Campbell, S., Kwok, K.C.S, Hitchcock, P.A, Tse, K.T., Leung, H.Y., Field measurements of natural periods of vibration and structural damping of wind-excited tall residential buildings. Wind and Structures, Vol. 10 (5), pp. 401-420, 2007.
• [10] CPWD, Handbook on seismic retrofit of buildings, Central Public Works Department & Indian Building Congress, In association with Indian Institute of Technology, Madras 2007.
• [11] Casciati, F., An overview of structural health monitoring expertise within the European Union, In: Wu, Z. S., Abe, M. (Editors), Structural Health Monitoring and Intelligent Infrastructure, pp. 31-37, Balkema 2003.
• [12] Chang, P. C., Flatau, A., Liu, S. C., Health monitoring of civil infrastructure, Structural Health Monitoring, Vol. 2 (3), pp. 257-267, 2003.
• [13] Cheung, M. S., Naumoski, N., The first smart long-span building in Canada - health monitoring of the Confederation Bridge, Proceedings of the 1st international workshop on structural health monitoring of innovative civil engineering structures, Mufti, A.A. (Editor), pp. 31-44, ISIS Canada Corporation, Winnipeg 2002.
• [14] Collobert, R., Sinz, F., Weston, J., and Bottou, L., Trading convexity for scalability, Proceedings of the 23rd International Conference on Machine Learning (ICML '06), pp. 201-208, Pittsburgh, USA 2006.
• [15] CTBUH, Council on Tall Building and Urban Habitat, The tallest 20 in 2020: entering the era of the megatall, Chicago 2011.
• [16] Cortes, C., Vapnik, V., Support-vector networks, Machine Learning, Vol. 20 (3), pp. 273-297, 1995 (doi:10.1007/BF00994018).
• [17] Cormen, T. H., Leiserson, C. E., Rivest, R. L., Introduction to Algorithms, MIT Press, Cambridge, MA 2001.
• [18] Denoon, R. O., Letchford, C. W., Kwok, K. C. S., Morrison, D. L., Field measurements of human reaction to wind-induced motion, Proceedings of 10th International Conference on Wind Engineering, Wind Engineering into the 21st Century, Copenhagen 21-24 June 1999, Balkema, Rotterdam 1999.
• [19] Day, W. H. E., Sankoff, D., Computational complexity of inferring phylogenies from dissimilarity matrices, Bulletin of Mathematical Biology, Vol. 35, pp. 224-231, 1986.
• [20] Day, W. H. E., Computational complexity of inferring phylogenies from dissimilarity matrices, Bulletin of Mathematical Biology, Vol. 49 (4), pp. 461-467, 1987.
• [21] Eddy, W., A new convex hull algorithm for planar sets, ACM Transactions on Mathematical Software, 3 (4), pp. 398–403, 1977.
• [22] Friswell, M. I., Penny, J. E. T., Is damage location using vibration measurements practical, Euromech 365 International Workshop: DAMAS 97, Structural Damage Assessment using Advanced Signal Processing Procedures, Sheffield (UK) 1997.
• [23] Forstner, E., Wenzel, H., The application of data mining in bridge monitoring projects: exploiting time series data of structural health monitoring, Proceedings of the 22nd International Workshop on Database and Expert Systems Applications, 2011.
• [24] Fujino ,Y., Abe, M., Structural health monitoring - current status and future, Proceedings of the 2nd European workshop on structural health monitoring, Boller, C., Staszewski, W. J. (Editors), pp. 3-10, Lancaster (PA), DEStech, 2004.
• [25] Graham, R. L., An efficient algorithm for determining the convex hull of a finite planar set, Information Processing Letters, Vol. 1 (4), pp. 132-133, 1972.
• [26] Guan, H., Karbhari, V. M., Sikorski, C. S., Time-domain output only modal parameter extraction and its application, Proceedings of the 1st BIOMASS Conference, Denmark2005.
• [27] Garvey, M. R., Johnson, D. S., Computers and Intractability: A guide to the theory of NP-completeness, A Series of Books in the Mathematical Sciences, Victor Klee (Editor), Freeman, New York 1979.
• [28] Graham, R. L., Foulds, L. R., Unlikelihood that minimal phyogenies for a realistic biological study can be constructed in reasonable computation time, Journal of Mathematical Biosciences, Vol. 60, pp. 133-142, 1982.
• [29] Haviland, R., A study of the uncertainties in the fundamental translational periods and damping values for real buildings, Massachusetts Institute of Technology, 275, PB-253, pp. 188, 1976.
• [30] Jarvis, R. A., On the identification of the convex hull of a finite set of points in the plane, Information Processing Letters, Vol. 2 (1), pp. 18-21, 1973.
• [31] Jeary, A.P., Damping in buildings a mechanism and a predictor, Earthquake Engineering and Structural Dynamics, Vol. 14, pp. 733-750, 1986.
• [32] Kallay, M., The complexity of incremental convex hull algorithms in RD, Information Processing Letters, Vol. 19 (4), pp. 197, 1984.
• [33] Kijewski-Correa, T., Kochly, M., Monitoring the wind-induced response of tall buildings: GPS performance and the issue of multipath effects, Journal of Wind Engineering and Industrial Aerodynamics, Vol. 95, pp. 1176-1198, 2007.
• [34] Kijewski-Correa, T., Kilpatrick, J., Kareem, A., Kwon, D. K., Bashor, R., Kochly, M., Young, B. S., Abdelrazaq, A., Galsworthy, J., Isyumov, N., Morrish, D., Sinn, R. C., Baker, W. F., Validating wind-induced response of tall buildings: Synopsis of the Chicago full-scale monitoring program, Vol. 132 (10), pp. 1509-1523, 2007.
• [35] Koh, H. M., Choo, J. F., Kim, S. K., Kim, C. Y., Recent application and development of structural health monitoring systems and intelligent structures in Korea. In: Structural health monitoring and intelligent infrastructure, Wu, Z. S., Abe, M., (Editors), pp. 99-111, Lisse, Balkema 2003.
• [36] Lanslots, J., Rodiers, B., Peeters, B., Automated pole-selection: proof-of-concept and validation, Proceedings of the International Conference on Noise and Vibration Engineering (ISAM) Leuven, Belgium 2004.
• [37] Lagomarsino, S., Forecast models for damping and vibration periods of buildings, Journal of Wind Engineering and Industrial Aerodynamics, Vol. 48, pp. 221-239, 1993.
• [38] Li, Q. S., Xiao, Y. Q., Wong, C. K., and Jeary, A. P., Field measurements of typhoon effects on a super tall building, Engineering Structures, Vol. 26 (2), pp.233-244, 2004.
• [39] Li, Q. S., Fu, J. Y, Xiao, Y. Q., Li, Z. N., Ni, Z. H., Xie, Z. N., Gu, M., Wind tunnel and full-scale study of wind effects on China’s tallest building, Engineering Structures, Vol. 28, pp. 1745-1758, 2006.
• [40] Li, Q. S., Zhi, L. H., Tuan, A. Y., Kao, C. S., Su, S. C., Wu, C. F., Dynamic Behavior of Taipei 101 Tower: field measurement and numerical analysis, Journal of Structural Engineering, ASCE, Vol. 137, pp. 143-155, 2011.
• [41] Mufti, A., Guidelines for structural health monitoring, University of Manitoba, ISIS, Canada 2001.
• [42] Mufti, A., A structural health monitoring of innovative Canadian civil engineering structures. Structural Health Monitoring, Vol. 1 (1), pp. 89-103, 2002.
• [43] Myrvoll, F., Aarnes, K. A., Larssen, R. M., Gjerding-Smith, K., Full scale measurements for design verification of bridges, In: Proceedings of the 18th International Modal Analytical Conference, pp. 827-835, Society for Experimental Mechanics, Bethel (CT) 2000.
• [44] NHAI, National Highways Authority of India Instrumentation (structural monitoring system) for Yamuna building at Allahabad/ Naini, Tender document, 2002 (http://www.nhai.org/ nit.htm).
• [45] Nigbor, R. L., Diehl, J. G., Two years’ experience using OASIS realtime remote condition monitoring system on two large buildings and bridges, In: Structural health monitoring: current status and perspectives, Chang F. K. (Editor), pp. 410-417, Technomic, Lancaster (PA) 1997.
• [46] Ou, J., The state-of-the-art and application of intelligent health monitoring systems for civil infrastructures in mainland of China, In: Progress in Structural Engineering, Mechanics and Computation, Zingoni, A., (ed.), pp. 599-608, Balkema/Taylor and Francis, London 2004.
• [47] Pines, D. J., Aktan, A. E., Status of structural health monitoring of longspan bridges in the United States, Progress in Structural Engineering and Materials, Vol. 4 (4), pp. 372-380, 2002.
• [48] Preparata, F. P., Hong, S. J., Convex hulls of finite sets of points in two and three dimensions, Communications of the ACM, Vol. 20 (2), pp. 87-93, 1977.
• [49] Rainieri, C., Fabbrocino, G., Cosenza E., Automated operational modal analysis as structural health monitoring tool: theoretical and applicative aspects, Key Engineering Materials, Vol. 347, pp. 479-484, 2007.
• [50] Satake, N., Suda, K., Arakawa, T., Sasaki, A., and Tamura, Y., Damping evaluation using full-scale data of buildings in Japan, Journal of Structural Engineering, Vol. 129 (4), pp. 470-477, 2003.
• [51] Soderstrom, T., Test of pole-zero cancellation in estimated models, Automatica, Vol. 11 (5), pp. 537-541, 1975.
• [52] Srinivasan, M. G., Kot, C. A., Effects of damage on the modal parameters of a cylindrical shell, Proceedings of the 10th International Modal Analysis Conference, pp. 529-535, 1992.
• [53] Thomson, P., Marulanda, C. J., Marulanda, A. J., Caicedo, J., Real time health monitoring of civil infrastructure systems in Colombia, In: Health Monitoring and Management of Civil Infrastructure Systems, Chase, S. B., Aktan, A. E. (Editors), pp. 113-121, The International Society for Optical Engineering, Bellingham (WA) 2001.
• [54] Valdiver, J. K., Detection of structural failure on fixed platforms by measurement of dynamic response, Publisher: Offshore Technology Conference, Document IDOTC-2267-MS. M.I.T. and Woods Hole Oceanographic Institution, 1975.
• [55] Wang, M. L., State-of-the-art applications in health monitoring, In: Invited presentation to Workshop on Basics of Structural Health Monitoring and Optical Sensing Technologies in Civil Engineering, Taiwan National Central University, pp. 113-142, 2004.
• [56] Wong, K. Y., Instrumentation and health monitoring of cable-supported bridges, In: Structural Control and Health Monitoring, Vol. 11 (2), pp. 91-124, 2004.
• [57] Worden, K., Dulieu-Barton, J. M., An overview of intelligent fault detection in systems and structures, International Journal of Structural Health Monitoring, Vol. 3, pp. 85-98, 2004.
• [58] Wu, Z.S., Structural health monitoring and intelligent infrastructures in Japan. In: Structural health monitoring and intelligent infrastructure, Wu, Z. S., Abe, M., (Editors), pp. 153-167, Lisse, Balkema, 2003.
• [59] Xiang, H.f., Health monitoring status of long-span bridges in China, In: Proceedings of the workshop on research and monitoring of long span bridge, pp. 24-31, 2000.
• [60] Yun, C. B., Lee, J. J., Kim, S. K., Kim, J. W., Recent R&D activities on structural health monitoring for civil infra-structures in Korea, KSCE Journal of Civil Engineering, Vol. 7 (6), pp. 637-651, 2003.