Smart Structures and Systems

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Impact force localization for civil infrastructure using augmented Kalman Filter optimization

  • Saleem, Muhammad M. (Department of Civil Engineering and Engineering Mechanics, The University of Arizona) ;
  • Jo, Hongki (Department of Civil Engineering and Engineering Mechanics, The University of Arizona)
  • Received : 2018.01.01
  • Accepted : 2019.01.16
  • Published : 2019.02.25
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Abstract

Impact forces induced by external object collisions can cause serious damages to civil engineering structures. While accurate and prompt identification of such impact forces is a critical task in structural health monitoring, it is not readily feasible for civil structures because the force measurement is extremely challenging and the force location is unpredictable for full-scale field structures. This study proposes a novel approach for identification of impact force including its location and time history using a small number of multi-metric observations. The method combines an augmented Kalman filter (AKF) and Genetic algorithm for accurate identification of impact force. The location of impact force is statistically determined in the way to minimize the AKF response estimate error at measured locations and then time history of the impact force is accurately constructed by optimizing the error co-variances of AKF using Genetic algorithm. The efficacy of proposed approach is numerically demonstrated using a truss and a plate model considering the presence of modelling error and measurement noises.

Keywords

Acknowledgement

Supported by : University of Engineering and Technology, Lahore

References

  1. Bishop, G. and Greg, W. (2001), "An introduction to the Kalman filter", Proc.of SIGGRAPH, Course, 8, North Carolina, USA.
  2. Buth, C.E., Williams, W.F., Brackin, M S., Lord, D., Geedipally, S. R. and Abu-Odeh, A.Y. (2010), "Analysis of large truck collisions with bridge piers: phase 1. Report of guidelines for designing bridge piers and abutments for vehicle collisions", Texas: Texas Transportation Institute.
  3. Busby, H.R. and Trujillo, D.M. (1997), "Optimal regularization of an inverse dynamics problem", Comput. Struct., 63(2), 243-248. https://doi.org/10.1016/S0045-7949(96)00340-9
  4. Choi, K.Y. and Chang, F.K. (1996), "Identification of impact force and location using distributed sensors", AIAA J., 34(1), 136-142. https://doi.org/10.2514/3.13033
  5. Coverley, P.T. and Staszewski, W.J. (2003), "Impact damage location in composite structures using optimized sensor triangulation procedure", Smart Mater. Struct., 12(5), 795-803. https://doi.org/10.1088/0964-1726/12/5/017
  6. Golub, G.H. and Von Matt, U. (1997), "Generalized crossvalidation for large-scale problems", J. Comput. Graph. Stat., 6(1), 1-34. https://doi.org/10.2307/1390722
  7. Guillaume, Patrick, et al. (2002), "An inverse method for the identification of localized excitation sources", Proceedings of the IMAC, Los Angeles, USA, February
  8. Hansen, P.C. (1992), "Analysis of discrete ill-posed problems by means of the L-curve", SIAM Review, 34(4), 561-580. https://doi.org/10.1137/1034115
  9. Inoue, H., Harrigan, J.J. and Reid, S.R. (2001), "Review of inverse analysis for indirect measurement of impact force", Appl. Mech. Rev., 54(6), 503-524. https://doi.org/10.1115/1.1420194
  10. Jacquelin, E., Bennani, A. and Hamelin, P. (2003), "Force reconstruction: analysis and regularization of a deconvolution problem", J. Sound Vib., 265(1), 81-107. https://doi.org/10.1016/S0022-460X(02)01441-4
  11. Juang, J.N. and Phan, M.Q. (2001), Identification and Control of Mechanical Systems, Cambridge University Press, Cambridge, England
  12. Khodabandeloo, B. and Jo, H.K. (2015), "Broadband dynamic load identification using augmented Kalman filter", Joint Conference AESE/ANCRiSST, Urbana, Illinois, USA, August.
  13. Kijewski-Correa, T., Su, S., Abittan, E. and Antsaklis, P.J. (2006), "On the use of heterogeneous, wireless sensor networks for damage assessment in bridges under unknown excitations", Proceedings of the 4th World Conference on Structural Control and Monitoring, San Diego, California, USA, July
  14. LeClerc, J.R. et al. (2007), "Impact detection in an aircraft composite panel - A neural-network approach", J. Sound Vib., 299(3), 672-682. https://doi.org/10.1016/j.jsv.2006.07.019
  15. Liu, J.J. et al. (2000), "Input force estimation of a cantilever plate by using a system identification technique", Comput. Method. Appl. M., 190(11), 1309-1322. https://doi.org/10.1016/S0045-7825(99)00465-X
  16. Lourens, E. et al. (2012), "An augmented Kalman filter for force identification in structural dynamics", Mech. Syst. Signal Pr., 27, 446-460. https://doi.org/10.1016/j.ymssp.2011.09.025
  17. Ma, C.K. and Lin, D.C. (2000), "Input forces estimation of a cantilever beam", Inverse Probl. Eng., 8(6), 511-528. https://doi.org/10.1080/174159700088027745
  18. Ma, C.K. et al. (1998), "A study of an inverse method for the estimation of impulsive loads", Int. J. Syst. Sci., 29(6), 663-672. https://doi.org/10.1080/00207729808929559
  19. Mahzan, S., Staszewski, W.J. and Worden, K. (2010), "Experimental studies on impact damage location in composite aerospace structures using genetic algorithms and neural networks", Smart Struct. Syst., 6(2), 147-165. https://doi.org/10.12989/sss.2010.6.2.147
  20. Mahzan, S. (2007), "Impact location in composite structures using advanced signal processing procedures", Ph.D. Dissertation, University of Sheffield, South Yorkshire, England.
  21. Meo, M. et al. (2005), "Impact identification on a sandwich plate from wave propagation responses", Compos. Struct., 71(3), 302-306. https://doi.org/10.1016/j.compstruct.2005.09.028
  22. Naets, F., Cuadrado, J. and Desmet, W. (2015), "Stable force identification in structural dynamics using Kalman filtering and dummy-measurements", Mech. Syst. Signal Pr., 50, 235-248 https://doi.org/10.1016/j.ymssp.2014.05.042
  23. Papadimitriou, C., Fritzen, C.P., Kraemer, P. and Ntotsios, E. (2011), "Fatigue predictions in entire body of metallic structures from a limited number of vibration sensors using Kalman filtering", Struct. Control Health Monit., 18(5), 554-573. https://doi.org/10.1002/stc.395
  24. Qiu, L. and Yuan, S. (2011), "A phase synthesis time reversal impact imaging method for on-line composite structure monitoring", Smart Struct. Syst., 8(3), 303-320 https://doi.org/10.12989/sss.2011.8.3.303
  25. Seydel, R. and Chang, F.K. (2001), "Impact identification of stiffened composite panels: I. System development", Smart Mater. Struct., 10(2), 354-369. https://doi.org/10.1088/0964-1726/10/2/323
  26. Sharif-Khodaei, Z., Ghajari, M. and Aliabadi, M.H. (2012), "Determination of impact location on composite stiffened panels", Smart Mater. Struct., 21(10), 105026(14pp) https://doi.org/10.1088/0964-1726/21/10/105026
  27. Sim, S.H., Spencer Jr., BF. and Nagayama, T. (2011), "Multimetric sensing for structural damage detection", J. Eng. Mech. - ASCE, 137(1), 22-30 https://doi.org/10.1061/(ASCE)EM.1943-7889.0000199
  28. Staszewski, W.J., Mahzan, S. and Traynor, R. (2009), "Health monitoring of aerospace composite structures-Active and passive approach", Compos. Sci. Technol., 69(11), 1678-1685. https://doi.org/10.1016/j.compscitech.2008.09.034
  29. Sung, D.U. et al. (2000), "Impact monitoring of smart composite laminates using neural network and wavelet analysis", J. Intel. Mat. Syst. Struct., 11(3), 180-190. https://doi.org/10.1106/N5E7-M37Y-3MAR-2KFH
  30. Worden, K. and Staszewski, W.J. (2000), "Impact location and quantification on a composite panel using neural networks and a genetic algorithm", Strain, 36(2), 61-68. https://doi.org/10.1111/j.1475-1305.2000.tb01175.x
  31. Yan, G. and Zhou, L. (2009), "Impact load identification of composite structure using genetic algorithms", J. Sound Vib., 319(3), 869-884. https://doi.org/10.1016/j.jsv.2008.06.051
  32. Yan, G., Sun, H. and Buyukozturk, O. (2017), "Impact load identification for composite structures using Bayesian regularization and unscented Kalman filter", Struct. Control Health Monit., 24(5)
  33. Zhang, X., Liang, D., Zeng, J. and Lu, J. (2014), "SVR model reconstruction for the reliability of FBG sensor network based on the CFRP impact monitoring", Smart Struct. Syst., 14(2), 145-158 https://doi.org/10.12989/sss.2014.14.2.145

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