Damage Localization for a Continuous Beam by the Displacement Variation

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Using the static displacement data, this paper presented a damage localization method for a continuous beam. This method is based on the estimation of changes in the static displacements of the structure. The most significant advantage of the method is that it does not require development of an analytical model of the structure being tested. All predictions are made directly from the measurments taken on the structure. The efficiency of the proposed method is demonstrated using simulated data of a three-span continuous beam. The results showed that the region in which the displacement variation is maximum is the damaged region for the continuous beam. Regardless of damages being small or large, the proposed method can identify locations of structural damages accurately only using the displacement changes under the applied static load. The proposed procedure is economical for computation and simple to implement. The presented scheme may be useful for damage localization of the continuous beam.

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366-369

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March 2015

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© 2015 Trans Tech Publications Ltd. All Rights Reserved

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[1] D. Wu, S. S. Law. Model error correction from truncated modal flexibility sensitivity and generic parameters. Ⅰ: Simulation. Mechanical Systems and Signal Processing, 18(6) (2004), pp.1381-1399.

DOI: 10.1016/s0888-3270(03)00094-3

Google Scholar

[2] D. Wu, S. S. Law. Eigen-parameter decomposition of element matrices for structural damage detection. Engineering Structures, 29 (2007), pp.519-528.

DOI: 10.1016/j.engstruct.2006.05.019

Google Scholar

[3] Q. W. Yang. A mixed sensitivity method for structural damage detection. Communications in Numerical Methods in Engineering, 25(4) (2009), pp.381-389.

DOI: 10.1002/cnm.1125

Google Scholar

[4] Q. W. Yang, J. K. Liu. Damage identification by the eigenparameter decomposition of structural flexibility change. International Journal for Numerical Methods in Engineering, 78(4) (2009), pp.444-459.

DOI: 10.1002/nme.2494

Google Scholar

[5] Q. W. Yang. A new damage identification method based on structural flexibility disassembly. Journal of Vibration and Control, 17(7) (2011), pp.1000-1008.

DOI: 10.1177/1077546309360052

Google Scholar

[6] X. Wang et al. Structural damage identification using static test data and changes in frequencies. Engineering Structures, 23 (2001), pp.610-621.

DOI: 10.1016/s0141-0296(00)00086-9

Google Scholar

[7] M. Sanayei, O. Onipede. Assessment of structures using static test data. AIAA J, 29(7) (1991), pp.1156-1179.

DOI: 10.2514/3.10720

Google Scholar

[8] M. R. Banan, M. R. Banna, K. D. Hjelmstad. Parameter estimation of structures from static response, Ⅰ: computational aspects. Journal of Structural Engineering, 120(11) (1994), pp.3243-3258.

DOI: 10.1061/(asce)0733-9445(1994)120:11(3243)

Google Scholar

[9] M. R. Banan, M. R. Banna, K. D. Hjelmstad. Parameter estimation of structures from static response, Ⅱ: numerical simulation studies. Journal of Structural Engineering, 120(11) (1994), pp.3259-3283.

DOI: 10.1061/(asce)0733-9445(1994)120:11(3259)

Google Scholar

[10] K. D. Hjelmstad, S. Shin. Damage detection and assessment of structures from static response. Journal of Engineering Mechanics, 123(6) (1997), pp.568-576.

DOI: 10.1061/(asce)0733-9399(1997)123:6(568)

Google Scholar

[11] J. H. Chou, Ghaboussi Jamshid. Genetic algorithm in structural damage detection. Computers and Structures, 79 (2001), pp.1335-1353.

DOI: 10.1016/s0045-7949(01)00027-x

Google Scholar

[12] F. Bakhtiari-Nejad, A. Rahai, A. Esfandiari. A structural damage detection method using static noisy data. Engineering Structures, 27 (2005), pp.1784-1793.

DOI: 10.1016/j.engstruct.2005.04.019

Google Scholar

[13] X. Z. Chen, H. P. Zhu, C. Y. Chen. Structural damage identification using test static data based on grey system theory. Journal of Zhejiang University SCIENCE, 6A(8) (2005), pp.790-796.

DOI: 10.1631/jzus.2005.a0790

Google Scholar

[14] B. Kouchmeshky, W. Aquino, J. C. Bongard et al. Co-evolutionary algorithm for structural damage identification using minimal physical testing. International Journal for Numerical Methods in Engineering, 69(5) (2007), pp.1085-1107.

DOI: 10.1002/nme.1803

Google Scholar