Model Updating-Based Approach for Damage Prognosis in Frames via Modal Residual Force

Authors: Gholamreza Ghodrati Amiri, Mojtaba Jafarian Abyaneh, Ali Zare Hosseinzadeh

Abstract:

This paper presents an effective model updating strategy for damage localization and quantification in frames by defining damage detection problem as an optimization issue. A generalized version of the Modal Residual Force (MRF) is employed for presenting a new damage-sensitive cost function. Then, Grey Wolf Optimization (GWO) algorithm is utilized for solving suggested inverse problem and the global extremums are reported as damage detection results. The applicability of the presented method is investigated by studying different damage patterns on the benchmark problem of the IASC-ASCE, as well as a planar shear frame structure. The obtained results emphasize good performance of the method not only in free-noise cases, but also when the input data are contaminated with different levels of noises.

Keywords: Frame, grey wolf optimization algorithm, modal residual force, structural damage detection.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1125801

References:

[1] A. Rytter, “Vibration based inspection of civil engineering structures,” PhD Thesis, Aalborg University, Denmark, 1993.
[2] W. Fan, and P. Qiao, “Vibration-based damage identification methods: a review and comparative study,” Struct. Health Monit., vol. 10, no. 1, pp. 83-111, Jan. 2011.
[3] J.T. Kim, and N. Stubbs, “Crack detection in beam-type structures using frequency data,” J. Sound Vib., vol. 259, no. 1, pp. 145-160, Jan. 2003.
[4] L.J. Jiang, J. Tang, and K.W. Wang, “An enhanced frequency-shift-based damage identification method using tunable piezoelectric transducer circuitry,” Smart Mater. Struct., vol. 15, no. 3, pp. 799-808, May 2006.
[5] M.A.B. Abdo, and M. Hori, “A numerical study of structural damage detection using changes in the rotation of mode shapes,” J. Sound Vib., vol. 251, no. 2, pp. 227-239, Mar. 2002.
[6] C.S. Hamey, W. Lestari, P. Qiao, and G. Song, “Experimental damage identification of carbon/epoxy composite beams using curvature mode shapes”. Struct. Health Monit., vol. 3, no. 4, pp. 333-353, Dec. 2004.
[7] W. Lestari, P.Z. Qiao, and S. Hanagud, “Curvature mode shape-based damage assessment of carbon/epoxy composite beams,” J. Intell. Mater. Syst. Struct., vol. 18, no. 3, pp. 189-208, Mar. 2007.
[8] F. Homaei, S. Shojaee, G. Ghodrati Amiri, “A direct damage detection method using multiple damage localization index based on mode shapes criterion,” Struct. Eng. Mech., Vol. 49, No. 2, pp. 183-202, Jan. 2014.
[9] T. You, P. Gardoni, and S. Hurlebaus, “Iterative damage index method for structural health monitoring,” Struct. Monit. Maint., vol. 1, no. 1, pp. 089-110, Mar. 2014.
[10] O. Yazdanpanah, S.M. Seyedpoor, and H. Akbarzadeh Bengar, “A new damage detection indicator for beams based on mode shape data,” Struct. Eng. Mech., vol. 53, no. 4, pp. 725-744, Feb. 2015.
[11] R. Perera, and R. Torres, "Structural damage detection via modal data with genetic algorithms." J. Struct. Eng., vol. 132, no. 9, pp. 1491-1501, Sep. 2006.
[12] O. Begambre, J.E. Laier, “A hybrid Particle Swarm Optimization – Simplex algorithm (PSOS) for structural damage identification,” Adv. Eng. Softw., vol. 40, pp. 883-891, Sept. 2009.
[13] G. Ghodrati Amiri, S.A. Seyed Razzaghi, and A. Bagheri, “Damage detection in plates based on pattern search and genetic algorithms,” Smart Struct. Syst., vol. 7, no. 2, pp. 117-132, Feb. 2011.
[14] F. Kang, J. Li, and X. Qing, “Damage detection based on improved particle swarm optimization using vibration data,” Appl. Soft Comput., vol. 12, no. 8, pp. 2329-2335, Aug. 2012.
[15] L. Vincenzi, G.D. Roeck, and M. Savoia, “Comparison between coupled local minimizers method and differential evolution algorithm in dynamic damage detection problems,” Adv. Eng. Softw., vol. 65, pp. 90-100, Nov. 2013.
[16] S.C. Mohan, A. Yadav, D.K. Maiti, and D. Maity, “A comparative study on crack identification of structures from the changes in natural frequencies using GA and PSO,” Eng. Computation, vol. 31, no. 7, pp. 1514-1531, 2014.
[17] G. Ghodrati Amiri, A. Zare Hosseinzadeh, S.A. Seyed Razzaghi, “Generalized flexibility-based model updating approach via democratic particle swarm optimization algorithm for structural damage”. Int. J. Optim. Civil Eng., vol. 5, no. 4, pp. 445-464, 2015.
[18] A. Zare Hosseinzadeh, G. Ghodrati Amiri, K.Y. Koo, “Optimization-based method for structural damage localization and quantification by means of static displacements computed by flexibility matrix,” Eng. Optimiz., vol. 48, no. 4, pp. 543-561, 2016.
[19] S. Mirjalili, S.M. Mirjalili, and A. Lewis, “Grey wolf optimizer,” Adv. Eng. Softw., vol. 69: pp. 46–61, Mar. 2014.
[20] M. Ge, E.M. Lui, and A.C. Khanse, “Non-proportional damage identification in steel frames,” Eng. Struct., vol. 32, no. 2, pp. 523-533, Feb. 2010.
[21] E.A. Johnson, H.F. Lam, L.S. Katafygiotis, and J.L. Beck, “Phase I IASC-ASCE Structural Health Monitoring Benchmark Problem using simulated data,” J. Eng. Mech., vol. 130, no. 1, pp. 3-15, Jan. 2004.