SPECIAL ISSUE ON THE 12TH INTERNATIONAL SYMPOSIUM ON STRUCTURAL ENGINEERING (ISSE-2012)No Access

ADAPTIVE-SCALE DAMAGE DETECTION FOR FRAME STRUCTURES USING BEAM-TYPE WAVELET FINITE ELEMENT: EXPERIMENTAL VALIDATION

SONGYE ZHU

Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hong Kong, P. R. China

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WEN-YU HE

Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hong Kong, P. R. China

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, and

WEI-XIN REN

School of Civil Engineering, Hefei University of Technology, Hefei, Anhui, P. R. China

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https://doi.org/10.1142/S1793431113500243Cited by:2 (Source: Crossref)

Abstract

The superior human vision system provides ingenious insight into an ideal damage detection strategy in which structural modeling scales are not only spatially varying but also dynamically changed according to actual needs. This paper experimentally examines the efficacy of a multi-scale damage detection method based on wavelet finite element model (WFEM). The beam-type wavelet finite element in this study utilizes the second-generation cubic Hermite multi-wavelets as interpolation functions. The dynamic testing results of a one-bay steel portal frame with multiple damages are employed in the experimental validation. Through a multi-stage updating of the WFEM, the multiple damages in the steel portal frame are detected in a progressive manner: the suspected region is first identified using a low-scale structural model, and the more accurate location and severity of the damage can be identified using a multi-scale model with local refinement. As the multi-scale WFEM considerably facilitates the adaptive change of modeling scales, the proposed multi-scale damage detection method can efficiently locate and quantify damage with minimal computation effort and a limited number of updating parameters and sensors, compared with conventional finite element methods.

Keywords:

References

K. Amaratunga and R. Sudarshan, Comput. Method Appl. Mech. Eng. 195, 2509 (2006), DOI: 10.1016/j.cma.2005.05.012. Web of Science, Google Scholar
Balageas, D., Fritzen, C. P. and Guemes, A. [2006] Structural Health Monitoring (ISTE USA, Newport Beach, CA, USA) . Google Scholar
R. Bogue, Sens. Rev. 29(2), 107 (2009), DOI: 10.1108/02602280910936200. Web of Science, Google Scholar
W. H. Chen and C. W. Wu, Comput. Mech. 16, 1 (1995), DOI: 10.1007/BF00369881. Web of Science, Google Scholar
Doebling, S. W., Farrar, C. R., Prime, M. B. and Shevitz, D. W. [1996] "Damage identification and health monitoring of structural mechanical systems from changes in their vibration characteristics: A literature review," Report No. LA-13070-MS, Los Alamos National Laboratory, Los Alamos, NM, USA . Google Scholar
S. Dubuque et al. , Bio-Inspired/Biomimetic Sensor Technologies and Applications , Proceedings of SPIE 7321 , eds. N. J. Fell and V. S. Swaminathan ( SPIE , 2009 ) . Google Scholar
W. Fan and P. Z. Qiao, Struct. Health Monit. 10(1), 83 (2011). Web of Science, Google Scholar
S. E. Fang, R. Perera and G. D. Roeck, J. Sound Vib. 313, 544 (2008), DOI: 10.1016/j.jsv.2007.11.057. Web of Science, Google Scholar
D. W. Fletcher-Holmes and A. R. Harvey, J. Opt. A, Pure Appl. Opt. 7, S298 (2005), DOI: 10.1088/1464-4258/7/6/007. Google Scholar
M. I. Friswell and J. E. Mottershead , Finite Element Model Updating in Structural Dynamics ( Kluwer Academic Publishers , Netherlands , 1995 ) . Google Scholar
C. P. Fritzen, D. Jannewein and T. Kiefer, Mech. Syst. Signal Process. 12, 163 (1998), DOI: 10.1006/mssp.1997.0139. Web of Science, Google Scholar
M. V. Gandhi and B. S. Thompson , Smart Materials and Structures ( Chapman and Hall , London, UK , 1992 ) . Google Scholar
H. Hao and Y. Xia, ASCE, J. Struct. Eng. 7, 222 (2002). Google Scholar
W. Y. He and W. X. Ren, Finite Elem. Anal. Des. 51, 59 (2012), DOI: 10.1016/j.finel.2011.11.005. Web of Science, Google Scholar
W. Y. He, W. X. Ren and Z. J. Yang, Fatigue Fract. Eng. Mater. Struct. 35, 732 (2012), DOI: 10.1111/j.1460-2695.2011.01626.x. Web of Science, Google Scholar
W. Y. He and W. X. Ren, Int. J. Struct. Stab. Dyn. 13(1), 1350007 (2013), DOI: 10.1142/S0219455413500077. Link, Web of Science, Google Scholar
W. Y. He and S. Zhu, Comput. Struct. 125, 177 (2013), DOI: 10.1016/j.compstruc.2013.05.001. Web of Science, Google Scholar
B. Jaishi and W. X. Ren, Mech. Syst. Signal Process. 21(5), 2295 (2007), DOI: 10.1016/j.ymssp.2006.09.008. Web of Science, Google Scholar
J. Ko, A. J. Kurdila and M. S. Pilant, Comput. Mech. 16, 235 (1995), DOI: 10.1007/BF00369868. Web of Science, Google Scholar
T. Lenau, H. Cheong and L. Shu, Sens. Rev. 28(4), 311 (2008), DOI: 10.1108/02602280810902604. Web of Science, Google Scholar
R. Perera and A. Ruiz, Mech. Syst. Signal Process. 22, 970 (2008), DOI: 10.1016/j.ymssp.2007.10.004. Web of Science, Google Scholar
Sohn, H., Farrar, C. R., Hemez, F. M., Shunk, D. D., Stinemates, D. W. and Nadler, B. R. [2004] "A review of structural health monitoring literature 1996–2001," Report No. LA-13976-MS, Los Alamos National Laboratory, Los Alamos, NM, USA . Google Scholar
A. Teughels and G. D. Roeck, J. Sound Vib. 278, 589 (2004), DOI: 10.1016/j.jsv.2003.10.041. Web of Science, Google Scholar
B. A. Wandell , Foundations of Vision ( Sinauer Associates , Sutherland, MA , 1995 ) . Google Scholar
Y. M. Wanget al., Int. J. Numer. Meth. Bio. 27, 562 (2011), DOI: 10.1002/cnm.1320. Web of Science, Google Scholar
Wikipedia [2012] "Fovea centralis." Wikipedia, The Free Encyclopedia, http://en. wikipedia.org/wiki/Fovea_centralis [accessed on 27 July 2012] . Google Scholar
Y. J. Yanet al., Mech. Syst. Signal Process. 21, 2198 (2007), DOI: 10.1016/j.ymssp.2006.10.002. Web of Science, Google Scholar
O. C. Zienkiewicz and R. L. Taylor, The Finite Element Method, 4th edn. (McGraw-Hill Book Company, London, 1961). Google Scholar