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A two-stage structural damage detection method using dynamic responses based on Kalman filter and particle swarm optimization

  • Beygzadeh, Sahar (Department of Civil Engineering, Shahid Bahonar University of Kerman) ;
  • Torkzadeh, Peyman (Department of Civil Engineering, Shahid Bahonar University of Kerman) ;
  • Salajegheh, Eysa (Department of Civil Engineering, Shahid Bahonar University of Kerman)
  • Received : 2022.02.10
  • Accepted : 2022.05.16
  • Published : 2022.09.10

Abstract

To solve the problem of detecting structural damage, a two-stage method using the Kalman filter and Particle Swarm Optimization (PSO) is proposed. In this method, the first PSO population is enhanced using the Kalman filter method based on dynamic responses. Due to noise in the sensor responses and errors in the damage detection process, the accuracy of the damage detection process is reduced. This method proposes a novel approach for solve this problem by integrating the Kalman filter and sensitivity analysis. In the Kalman filter, an approximate damage equation is considered as the equation of state and the damage detection equation based on sensitivity analysis is considered as the observation equation. The first population of PSO are the random damage scenarios. These damage scenarios are estimated using a step of the Kalman filter. The results of this stage are then used to detect the exact location of the damage and its severity with the PSO algorithm. The efficiency of the proposed method is investigated using three numerical examples: a 31-element planer truss, a 52-element space dome, and a 56-element space truss. In these examples, damage is detected for several scenarios in two states: using the no noise responses and using the noisy responses. The results show that the precision and efficiency of the proposed method are appropriate in structural damage detection.

Keywords

References

  1. Alkayem, N.F., Cao, M., Zhang, Y., Bayat, M. and Su, Z. (2018), "Structural damage detection using finite element model updating with evolutionary algorithms: A survey", Neur. Comput. Appl., 30, 389-411. https://doi.org/10.1007/s00521-017-3284-1.
  2. Arabha Najafabadi, A., Daneshjoo, F. and Ahmadi, H.R. (2020), "Multiple damage detection in complex bridges based on strain energy extracted from single point measurement", Front. Struct. Civil Eng., 14, 722-730. https://doi.org/10.1007/s11709-020-0624-5.
  3. Beygzadeh, S., Salajegheh, E., Torkzadeh, P., Salajegheh, J. and Naseralavi, S.S. (2014), "An improved genetic algorithm for optimal sensor placement in space structures damage detection", Int. J. Space Struct., 29(3), 121-136. https://doi.org/10.1260/0266-3511.29.3.121.
  4. Ding, Z., Lu, Z., Huang, M. and Liu, J. (2016), "Improved artificial Bee Colony algorithm for crack identification in beam using natural frequencies only", Inverse Probl. Sci. Eng., 25(2), 218-238. https://doi.org/10.1080/17415977.2016.1160391.
  5. Ding, Z.H., Huang, M. and Lu, Z.R. (2016), "Structural damage detection using artificial bee colony algorithm with hybrid search strategy", Swarm Evol. Comput., 28, 1-13. https://doi.org/10.1016/j.swevo.2015.10.010.
  6. Dinh-Cong, D. and Nguyen-Thoi, T. (2021), "A new efficient twostage method for damage localization and quantification in shell structures", Appl. Soft Comput., 108, 107468. https://doi.org/10.1016/j.asoc.2021.107468.
  7. Dinh-Cong, D., Nguyen-Thoi, T. and Nguyen-Thai, D. (2021), "A two-stage multi-damage detection approach for composite structures using MKECR-Tikhonov regularization iterative method and model updating procedure", Appl. Math. Model., 90, 114-130. https://doi.org/10.1016/j.apm.2020.09.002.
  8. Dinh-Cong, D., Nguyen-Thoi, T. and Nguyen-Thai, D. (2020), "A FE model updating technique based on SAP2000-OAPI and enhanced SOS algorithm for damage assessment of full-scale structures", Appl. Soft Comput., 89, 106100. https://doi.org/10.1016/j.asoc.2020.106100.
  9. Dinh-Cong, D., Nguyen-Thoi, T., Vinyas, M. and Nguyen, D. (2019), "Two-stage structural damage assessment by combining modal kinetic energy change with symbiotic organisms search", Int. J. Struct. Stab. Dyn., 19(10), 1950120. https://doi.org/10.1142/S0219455419501207.
  10. Dinh-Cong, D., Pham-Toan, T., Nguyen-Thai, D. and NguyenThoi, T. (2019), "Structural damage assessment with incomplete and noisy modal data using model reduction technique and LAPO algorithm", Struct. Infrastr. Eng., 15 (11), 1436-1449. https://doi.org/10.1080/15732479.2019.1624785.
  11. Dinh-Cong, D., Vo-Duy, T. and Nguyen-Thoi, T. (2018), "Damage assessment in truss structures with limited sensors using a two-stage method and model reduction", Appl. Soft Comput., 66, 264-277. https://doi.org/10.1016/j.asoc.2018.02.028.
  12. Dinh-Cong, D., Vo-Duy, T., Ho-Huu, V., Dang-Trung, H. and Nguyen-Thoi, T. (2017), "An efficient multi-stage optimization approach for damage detection in plate structures", Adv. Eng. Soft., 112, 76-87. https://doi.org/10.1016/j.advengsoft.2017.06.015.
  13. Dinh-Cong, D., Vo-Duy, T., Nguyen-Minh, N., Ho-Huu, V. and Nguyen-Thoi, T. (2017), "A two-stage assessment method using damage locating vector method and differential evolution algorithm for damage identification of cross-ply laminated composite beams", Adv. Struct. Eng., 20(12), 1807-1827. https://doi.org/10.1177/1369433217695620.
  14. Gerist, S. and Maheri, M.R. (2016), "Multi-stage approach for structural damage detection problem using basis pursuit and particle swarm optimization", J. Sound Vib., 384, 210-226. https://doi.org/10.1016/j.jsv.2016.08.024.
  15. He, J., Zhang, X., Feng, Z., Chen, Z. and Cao, Z. (2020), "A twostage Kalman filter for the identification of structural parameters with unknown loads", Smart Struct. Syst., 26(6), 693-701. https://doi.org/10.12989/sss.2020.26.6.693.
  16. Huang, J., Li, D., Zhang, C. and Li, H. (2019), "Improved Kalman filter damage detection approach based on lp regularization", Struct. Control Hlth. Monit., 26(10), e2424. https://doi.org/10.1002/stc.2424.
  17. Jena, P.K. and Parhi, D.R. (2015), "A modified particle swarm optimization technique for crack detection in cantilever beams", Arab. J. Sci. Eng., 40, 3263-3272. https://doi.org/10.1007/s13369-015-1661-6.
  18. Jin, C., Jang, S. and Sun, X. (2015), "Structural damage detection using extended Kalman filter combined with statistical process control", Proceedings of SPIE 9435. Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems, 9435, 755-764.
  19. Jin, C., Jang, S. and Sun, X. (2017) "An integrated real-time structural damage detection method based on extended Kalman filter and dynamic statistical process control", Adv. Struct. Eng., 20(4), 549-563. https://doi.org/10.1177/1369433216658484.
  20. Kang, F., Li, J. and Xu, Q. (2012), "Damage detection based on improved particle swarm optimization using vibration data", Appl. Soft. Comput., 12(8), 2329-2335. https://doi.org/10.1016/j.asoc.2012.03.050.
  21. Kaveh, A. and Maniat, M. (2015), "Damage detection based on MCSS and PSO using modal data", Smart Struct. Syst., 15(5), 1253-1270. https://doi.org/10.12989/sss.2015.15.5.1253.
  22. Kennedy, J. and Eberhartm R. (1995), "Particle swarm optimization", Proceedings of IEEE International Conference on Neural Network, 1942-1948.
  23. Lai, Z., Lei, Y., Zhu, S., Xu, Y.L., Zhang, X.H. and Krishnaswamy, S. (2016), "Moving-window extended Kalman filter for structural damage detection with unknown process and measurement noises", Measure., 88, 428-440. https://doi.org/10.1016/j.measurement.2016.04.016.
  24. Le, H.Q., Truong, T.T., Dinh-Cong, D. and Nguyen-Thoi, T. (2021), "A deep feed-forward neural network for damage detection in functionally graded carbon nanotube-reinforced composite plates using modal kinetic energy", Front. Struct. Civil Eng., 15, 1453-1479. https://doi.org/10.1007/s11709-021-0767-z.
  25. Lei, Y., Lai, Z., Zhu, S. and Zhang, X. (2014), "Experimental study on impact-induced damage detection using an improved extended Kalman filter", Int. J. Struct. Stab. Dyn., 14(5), 1440007. https://doi.org/10.1142/S0219455414400070.
  26. Li, J., Zhu, X., Law, S. and Samali, B. (2020), "A two-step driveby bridge damage detection using dual Kalman filter", Int. J Struct. Stab. Dyn., 20(10), 2042006. https://doi.org/10.1142/S0219455420420067.
  27. Li, S. and Lu, Z.R. (2015), "Multi-swarm fruit fly optimization algorithm for structural damage identification", Struct. Eng. Mech., 56(3), 409-422. https://doi.org/10.12989/sem.2015.56.3.409.
  28. Messina, A., Williams, E.J. and Contursi, T. (1998), "Structural damage detection by a sensitivity and statistical-based method", J. Sound Vib., 216(5), 791-808. https://doi.org/10.1006/jsvi.1998.1728.
  29. Naseralavi, S.S., Salajegheh, E., Salajegheh, J. and Fadaee, M.J. (2012), "Detection of damage in cyclic structures using an eigenpair sensitivity matrix", Comput. Struct., 110-111, 43-59. https://doi.org/10.1016/j.compstruc.2012.06.003.
  30. Nasr, D.E. and Saad, G.A. (2017), "Optimal sensor placement using a combined genetic algorithm-Ensemble Kalman filter framework", ASCE-ASME J. Risk Uncertain. Eng. Syst. Part A: Civil Eng., 3(1), 1-14. https://doi.org/10.1061/AJRUA6.0000886.
  31. Nouri Shirazi, M.R., Mollamahmoudi, H. and Seyedpoor, S.M. (2014), "Structural damage identification using an adaptive multi-stage optimization method based on a modified particle swarm algorithm", J. Optim. Theor. Appl., 160(3), 1009-1019. https://doi.org/10.1007/s10957-013-0316-6.
  32. Pahnabi, N. and Seyedpoor, S.M. (2021), "Damage identification in connections of moment frames using time domain responses and an optimization method", Front. Struct. Civil Eng., 15, 851-866. https://doi.org/10.1007/s11709-021-0739-3.
  33. Pandey, A.K. and Biswas, M. (1995), "Damage diagnosis of truss structures by estimation of flexibility change", Int. J. Anal. Exper. Modal Anal., 10(2), 104-117.
  34. Ramezani, M. and Bahar, O. (2021), "Structural damage identification for elements and connections using an improved genetic algorithm", Smart Struct. Syst., 28(5), 643-660. https://doi.org/10.12989/sss.2021.28.5.643.
  35. Seyedpoor, S.M. (2012), "A two stage method for structural damage detection using a modal strain energy based index and particle swarm optimization", Int. J. Nonlin. Mech., 47(1), 1-8. https://doi.org/10.1016/j.ijnonlinmec.2011.07.011.
  36. Wei, Z., Liu, J. and Lu, Z. (2018), "Structural damage detection using improved particle swarm optimization", Inverse Prob. Sci. Eng., 26(6), 792-810. https://doi.org/10.1080/17415977.2017.1347168.
  37. Xu, H.J., Ding, Z.H., Lu, Z.R. and Liu, J.K. (2015), "Structural damage detection based on chaotic artificial bee colony algorithm", Struct. Eng. Mech., 55(6), 1223-1239. https://doi.org/10.12989/sem.2015.55.6.1223.
  38. Xu, H.J., Liu, J.K. and Lu, Z.R. (2016), "Structural damage identification based on cuckoo search algorithm", Adv. Struct. Eng., 19(5), 849-859. https://doi.org/10.1177/1369433216630128.
  39. Yang, J.N., Lin, S., Huang, H. and Zhou, L. (2006), "An adaptive extended Kalman filter for structural damage identification", Struct. Control Hlth. Monit., 13(4), 849-867. https://doi.org/10.1002/stc.84.
  40. Yun, D.Y., Hong, T., Lee, D. and Park, H.S. (2021), "Structural damage identification with a Tuning-free hybrid extended Kalman filter", Struct. Eng. Int., 31(3), 391-405. https://doi.org/10.1080/10168664.2020.1797614.