- Volume 8 Issue 4
DOI QR Code
Bayesian structural damage detection of steel towers using measured modal parameters
- Lam, Heung-Fai (Department of Architecture and Civil Engineering, City University of Hong Kong) ;
- Yang, Jiahua (Department of Architecture and Civil Engineering, City University of Hong Kong)
- Received : 2014.04.04
- Accepted : 2014.09.18
- Published : 2015.04.25
Structural Health Monitoring (SHM) of steel towers has become a hot research topic. From the literature, it is impractical and impossible to develop a "general" method that can detect all kinds of damages for all types of structures. A practical method should make use of the characteristics of the type of structures and the kind of damages. This paper reports a feasibility study on the use of measured modal parameters for the detection of damaged braces of tower structures following the Bayesian probabilistic approach. A substructure-based structural model-updating scheme, which groups different parts of the target structure systematically and is specially designed for tower structures, is developed to identify the stiffness distributions of the target structure under the undamaged and possibly damaged conditions. By comparing the identified stiffness distributions, the damage locations and the corresponding damage extents can be detected. By following the Bayesian theory, the probability model of the uncertain parameters is derived. The most probable model of the steel tower can be obtained by maximizing the probability density function (PDF) of the model parameters. Experimental case studies were employed to verify the proposed method. The contributions of this paper are not only on the proposal of the substructure-based Bayesian model updating method but also on the verification of the proposed methodology through measured data from a scale model of transmission tower under laboratory conditions.
Bayesian approach;damage detection;steel tower;modal identification;model updating
Supported by : Council of the Hong Kong Special Administrative Region
- Au, S.K. (2011a), "Fast Bayesian FFT method for ambient modal identification with separated modes", J. Eng. Mech., ASCE, 137(3), 214-226. https://doi.org/10.1061/(ASCE)EM.1943-7889.0000213
- Au, S.K. (2011b), "Assembling mode shapes by least squares", Mech. Syst. Sig. Proc., 25(1), 163-179. https://doi.org/10.1016/j.ymssp.2010.08.002
- Au, S.K., Ni, Y.C., Zhang, F.L. and Lam, H.F. (2012), "Full-scale dynamic testing and modal identification of a coupled floor slab system", Eng. Struct., 37, 167-178. https://doi.org/10.1016/j.engstruct.2011.12.024
- Au, S.K and Zhang, F.L. (2012), "Ambient modal identification of a primary-secondary structure using fast Bayesian FFT approach", Mech. Syst. Signal Pr., 28, 280-296. https://doi.org/10.1016/j.ymssp.2011.07.007
- Beck, J.L. (1978), "Determining models of structures from earthquake records", Earthquake Engineering Research Laboratory, California Institute of Technology, Pasadena.
- Beck, J.L. and Katafygiotis, L.S. (1998), "Updating models and their uncertainties. I: Bayesian statistical framework", J. Eng. Mech., ASCE, 124(4), 455-461. https://doi.org/10.1061/(ASCE)0733-9399(1998)124:4(455)
- Burdekin, F.M. (1993), "Nondestructive testing of welded structural steelwork", Proc. Inst. Civ. Eng. Struct., 99(1), 89-95. https://doi.org/10.1680/istbu.1993.22557
- ChinaFotoPress/Getty Images AsiaPac (2011), Eight Dead in Sichuan Transmission Tower Collapse, http://www.zimbio.com/pictures/2FVBZhPqCwD/Eight+Dead+Sichuan+Transmission+Tower+Collapse/hOm95DMn5qb.
- Magix (2008), Energy deregulation forces wide scale distributed energy, http://mgx.com/blogs/2008/03/30/energy-deregulation-forces-wide-scale-distributed-energy/.
- Katafygiotis, L.S. and Beck, J.L. (1998), "Updating models and their uncertainties. II: Model identifiability", J. Eng. Mech., ASCE, 124(4), 463-467. https://doi.org/10.1061/(ASCE)0733-9399(1998)124:4(463)
- Lam, H.F., Katafygiotis, L.S. and Mickleborough, N.C. (2004), "Application of a statistical model updating approach on Phase I of the IASC-ASCE structural health monitoring benchmark study", J. Eng. Mech., ASCE, 130(1), 34-48. https://doi.org/10.1061/(ASCE)0733-9399(2004)130:1(34)
- Lam, H.F., Ng, C.T. and Leung, A.Y.T. (2008), "Multicrack detection on semirigidly connected beams utilizing dynamic data", J. Eng. Mech., ASCE, 134(1), 90-99. https://doi.org/10.1061/(ASCE)0733-9399(2008)134:1(90)
- Lam, H.F. and Ng, C.T. (2008), "The selection of pattern features for structural damage detection using an extended Bayesian ANN algorithm", Eng. Struct., 30(10), 2762-2770. https://doi.org/10.1016/j.engstruct.2008.03.012
- Lam, H.F. and Yin, T. (2011), "Dynamic reduction-based structural damage detection of transmission towers: Practical issues and experimental verification", Eng. Struct., 33(5), 1459-1478. https://doi.org/10.1016/j.engstruct.2011.01.009
- Li, X.Y. and Law, S.S. (2010), "Matrix of covariance of covariance of acceleration responses for damage detection from ambient vibration measurements", Mech. Syst. Signal Pr., 24(4), 945-956. https://doi.org/10.1016/j.ymssp.2009.10.007
- Kassimali, A. (2011), Matrix analysis of structures, Cengage Learning.
- Kim, J.H., Jeon, H.S. and Lee, C.W. (1992), "Application of the modal assurance criteria for detecting and locating structural faults", Proceedings of the 10th International Modal Analysis Conference, SEM Society for Experimental Mechanics Inc.
- O'Callahan, J., Avitabile, P. and Riemer, R. (1989), "System equivalent reduction expansion process (SEREP)", Proceedings of the 7th international modal analysis conference, Schnectady, Union College, NY, 1, 29-37.
- Papadimitriou, C. and Papadioti, D.C. (2013), "Component mode synthesis techniques for finite element model updating", Comput. Struct., 126, 15-28. https://doi.org/10.1016/j.compstruc.2012.10.018
- Popovics, J.S. and Rose, J.L. (1994), "A survey of developments in ultrasonic NDE of concrete", Transactions on Ferroelectrics and Freq. Control, IEEE, 44(1), 140-143.
- Vanik, M.W., Beck, J.L. and Au, S.K. (2000), "Bayesian probabilistic approach to structural health monitoring", J. Eng. Mech., ASCE, 126(7), 738-745. https://doi.org/10.1061/(ASCE)0733-9399(2000)126:7(738)
- Yin, T., Lam, H.F., Chow, H.M. and Zhu, H.P. (2009), "Dynamic reduction-based structural damage detection of transmission tower utilizing ambient vibration data", Eng. Struct., 31(9), 2009-2019. https://doi.org/10.1016/j.engstruct.2009.03.004
- Yaglom, A.M. (1987), Correlation theory of stationary and related random functions, Springer-Verlag, Berlin, Germany.
- Yang, J.N., Lei, Y., Lin, S. and Huang, N. (2004), "Hilbert-Huang based approach for structural damage detection", J. Eng. Mech., 130(1), 85-95. https://doi.org/10.1061/(ASCE)0733-9399(2004)130:1(85)
- Yuen, K.V., Katafygiotis, L.S. and Beck, J.L. (2002), "Spectral density estimation of stochastic vector processes", Prob. Eng. Mech., 17(3), 265-272. https://doi.org/10.1016/S0266-8920(02)00011-5
- Zhong, S.C. and Oyadiji, S.O. (2011), "Detection of cracks in simply-supported beams by continuous wavelet transform of reconstructed modal data", Comput. Struct., 89(1-2), 127-148. https://doi.org/10.1016/j.compstruc.2010.08.008
- Zimmerman, D.C. and Kaouk, M. (1994), "Structural damage detection using a minimum rank update theory", J. Vib. Acoust., 116, 222-231. https://doi.org/10.1115/1.2930416
- Ambient Vibration Test, Modal Identification and Structural Model Updating Following Bayesian Framework vol.15, pp.07, 2015, https://doi.org/10.1142/S0219455415400246
- Model updating of suspended-dome using artificial neural networks vol.20, pp.11, 2017, https://doi.org/10.1177/1369433217693629
- Damage detection of beam structures using quasi-static moving load induced displacement response vol.145, 2017, https://doi.org/10.1016/j.engstruct.2017.05.009
- A probabilistic approach for quantitative identification of multiple delaminations in laminated composite beams using guided waves vol.127, 2016, https://doi.org/10.1016/j.engstruct.2016.08.052
- Two-Mass Vehicle Model for Extracting Bridge Frequencies 2017, https://doi.org/10.1142/S0219455418500566
- Active vibration-based structural health monitoring system for wind turbine blade: Demonstration on an operating Vestas V27 wind turbine vol.16, pp.5, 2017, https://doi.org/10.1177/1475921717722725
- Identification of rail-sleeper-ballast system through time-domain Markov chain Monte Carlo-based Bayesian approach vol.140, 2017, https://doi.org/10.1016/j.engstruct.2017.03.001
- Operational modal identification and finite element model updating of a coupled building following Bayesian approach vol.25, pp.2, 2018, https://doi.org/10.1002/stc.2089
- Structural damage detection using finite element model updating with evolutionary algorithms: a survey 2017, https://doi.org/10.1007/s00521-017-3284-1
- Consistent Multilevel RDT-ERA for Output-Only Ambient Modal Identification of Structures vol.17, pp.09, 2017, https://doi.org/10.1142/S0219455417501061
- Structural Nonlinear Damage Detection Method Using AR/ARCH Model vol.17, pp.08, 2017, https://doi.org/10.1142/S0219455417500833
- Entropy-Based Structural Health Monitoring System for Damage Detection in Multi-Bay Three-Dimensional Structures vol.20, pp.1, 2018, https://doi.org/10.3390/e20010049
- Bayesian model updating of a coupled-slab system using field test data utilizing an enhanced Markov chain Monte Carlo simulation algorithm vol.102, 2015, https://doi.org/10.1016/j.engstruct.2015.08.005
- Markov chain Monte Carlo-based Bayesian method for structural model updating and damage detection 2018, https://doi.org/10.1002/stc.2140
- An efficient adaptive sequential Monte Carlo method for Bayesian model updating and damage detection pp.15452255, 2018, https://doi.org/10.1002/stc.2260
- A procedure for the identification of multiple cracks on beams and frames by static measurements vol.25, pp.8, 2018, https://doi.org/10.1002/stc.2194
- Damage Identification of Periodically-Supported Structures Following the Bayesian Probabilistic Approach pp.1793-6764, 2018, https://doi.org/10.1142/S021945541940011X
- Dynamic Property Evaluation of a Long-Span Cable-Stayed Bridge (Sutong Bridge) by a Bayesian Method pp.1793-6764, 2018, https://doi.org/10.1142/S0219455419400108
- Uncertainty Quantification of Load Effects under Stochastic Traffic Flows pp.1793-6764, 2018, https://doi.org/10.1142/S0219455419400091