A Two-Stage Scheme for Plate Damage Identification Based on Lock-in Thermography and Dynamic Analysis

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Abstract:

This paper presents a two-stage scheme of damage identification for plate-type structure. In the first stage, probable damaged regions and their relative severities can be detected based on lock-in thermography technique. In the second stage, the relation between the damage level and its corresponding natural frequencies of the plate is constructed by means of Kriging surrogate model based on dynamic analysis. The inverse problem of damage quantification over the surrogate model is then solved by using a robust stochastic particle swarm optimization algorithm. Experimental study on a double-damaged plate demonstrates the feasibility and effectiveness of the proposed scheme.

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Key Engineering Materials (Volumes 569-570)

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839-846

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July 2013

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© 2013 Trans Tech Publications Ltd. All Rights Reserved

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[1] Liu X, Lieven NAJ, Escamilla A PJ. Frequency response function shape based methods for structural damage localization. Mech Syst Signal Pr 2009; 23: 1243-59.

DOI: 10.1016/j.ymssp.2008.10.002

Google Scholar

[2] Doebling SW, Farrar CR, Prime MB. A summary review of vibration-based damage identification methods. The Shock and Vibration Digest 1998; 30(2): 91-105.

DOI: 10.1177/058310249803000201

Google Scholar

[3] Nandwana BP, Maiti SK. Detection of the location and size of a crack in stepped cantilever beams based on measurements of natural frequencies. J Sound Vib 1997; 203(3): 435-46.

DOI: 10.1006/jsvi.1996.0856

Google Scholar

[4] Chaudhari TD, Maiti SK. A study of vibration of geometrically segmented beams with and without crack. Int J Solids Struct 2000; 37(5): 761-79.

DOI: 10.1016/s0020-7683(99)00054-2

Google Scholar

[5] Ratcliffe CP. A frequency and curvature based experimental method for locating damage in structures. J Vib Acoust 2000; 122: 324-29.

Google Scholar

[6] Zhang Z, Aktan AE. Application of modal flexibility and its derivatives in structural identification. Research in Nondestructive Evaluation 1998; 10 (1): 43-61.

DOI: 10.1080/09349849809409622

Google Scholar

[7] Wu D, Law SS. Damage localization in plate structures from uniform load surface curvature. J Sound Vib 2004; 267: 227-44.

DOI: 10.1016/j.jsv.2003.07.040

Google Scholar

[8] Yoon MK, Heider D, Gillespie JW, Ratcliffe CP, Crane RM. Local damage detection using the two-dimensional gapped smoothing method. J Sound Vib 2005; 279: 119-39.

DOI: 10.1016/j.jsv.2003.10.058

Google Scholar

[9] Pickering S, Almond D. Matched excitation energy comparison of the pulse and lock-in thermography NDE techniques. NDT&E International 2008; 41: 501-9.

DOI: 10.1016/j.ndteint.2008.05.007

Google Scholar

[10] Meola C, Carlomagno G M, Squillace A, et al. Non-destructive evaluation of aerospace materials with lock-in thermography[J]. Engineering Failure Analysis, 2006, 13(3): 380-388.

DOI: 10.1016/j.engfailanal.2005.02.007

Google Scholar

[11] Choi M, Kang K, Park J, Kim W, Kim K. Quantitative determination of a subsurface defect of reference specimen by lock-in infrared thermography. NDT&E International 2008; 41: 119-24.

DOI: 10.1016/j.ndteint.2007.08.006

Google Scholar

[12] Saintey MB, Almond DP. An artificial neural network interpreter for transient thermography image data. NDT&E International 1997; 30(5): 291-5.

DOI: 10.1016/s0963-8695(96)00071-0

Google Scholar

[13] Ludwig N, Teruzzi P. Heat losses and 3D diffusion phenomena for defect sizing procedures in video pulse thermography. Infrared Physics & Technology 2002; 43: 297-301.

DOI: 10.1016/s1350-4495(02)00155-x

Google Scholar

[14] Fang SE, Perera R. Damage identification by response surface based model updating using D-optimal design. Mech Syst Signal Pr 2011; 25(2): 717-33.

DOI: 10.1016/j.ymssp.2010.07.007

Google Scholar

[15] Shyy W, Papila N, Vaidyanathan R, Tucker K. Global design optimization for aerodynamics and rocket propulsion components. Prog Aerospace Sci 2001; 37(1): 59-118.

DOI: 10.1016/s0376-0421(01)00002-1

Google Scholar

[16] Gao YH, Turng LS, Wang XC. Adaptive geometry and process optimization for injection molding using kriging surrogate model trained by numerical simulation. Adv Poly Tech 2008; 26(5): 1-16.

DOI: 10.1002/adv.20116

Google Scholar

[17] Cundy AL. Use of response surface metamodels in damage identification of dynamic structures. Master Thesis: Virgina Polytechnic Institute and State University (2002).

Google Scholar

[18] Faravelli L, Casciati S. Structural damage detection and localization by response change diagnosis. Struct Saf Reliab 2004; 6: 104-15.

DOI: 10.1002/pse.171

Google Scholar

[19] Simpson TW, Poplinski JD, Koch PN, Allen JK. Meta-models for computer-based engineering design: survey and recommendations. Eng Comput 2001; 17(2): 129-50.

DOI: 10.1007/pl00007198

Google Scholar

[20] Wu D, Busse C. Lock-in thermography for nondestructive evaluation of materials. Rev Gén Therm 1998; 37: 693-703.

Google Scholar

[21] Sacks J, Welch WJ, Mitchell TJ, Wynn HP. Design and analysis of computer experiments. Stat Sci 1989; 4(4): 409-35.

Google Scholar

[22] Sakata S, Ashida F, Zhao M. On applying Kriging-based approximate optimization to inaccurate data. Comput Meth Appl Mech Eng 2007; 196(13-16): 2055-69.

DOI: 10.1016/j.cma.2006.11.004

Google Scholar

[23] Ren WX, Chen HB. Finite element model updating in structural dynamics by using the response surface method. Eng Struct 2010; 32: 2455-65.

DOI: 10.1016/j.engstruct.2010.04.019

Google Scholar

[24] Qi H, Ruan LM, Zhang HC, Wang YM, Tan HP. Inverse radiation analysis of a one-dimensional participating slab by stochastic particle swarm optimizer algorithm. Int J Therm Sci 2007; 46: 649-61.

DOI: 10.1016/j.ijthermalsci.2006.10.002

Google Scholar