Structural Engineering and Mechanics

  • 제65권1호
  • /
  • Pages.43-51
  • /
  • 2018
  • /
  • 1225-4568(pISSN)
  • /
  • 1598-6217(eISSN)
테크노프레스 (Techno-Press)
권호 표지
DOI QR코드

DOI QR Code

Analysis of thermal and damage effects over structural modal parameters

  • Ortiz Morales, Fabricio A. (Department of Civil Engineering, Federal University of Ouro Preto) ;
  • Cury, Alexandre A. (Department of Applied and Computational Mechanics, Federal University of Juiz de Fora)
  • 투고 : 2017.04.02
  • 심사 : 2017.11.02
  • 발행 : 2018.01.10
⟨ 이전 논문 다음 논문 ⟩

초록

Structural modal parameters i.e. natural frequencies, damping ratios and mode shapes are dynamic features obtained either by measuring the vibration responses of a structure or by means of finite elements models. Over the past two decades, modal parameters have been used to detect damage in structures by observing its variations over time. However, such variations can also be caused by environmental factors such as humidity, wind and, more importantly, temperature. In so doing, the use of modal parameters as damage indicators can be seriously compromised if these effects are not properly tackled. Many researchers around the world have found numerous methods to mitigate the influence of such environmental factors from modal parameters and many advanced damage indicators have been developed and proposed to improve the reliability of structural health monitoring. In this paper, several vibration tests are performed on a simply supported steel beam subjected to different damage scenarios and temperature conditions, aiming to describe the variation in modal parameters due to temperature changes. Moreover, four statistical methodologies are proposed to identify damage. Results show a slightly linear decrease in the modal parameters due to temperature increase, although it is not possible to establish an empirical equation to describe this tendency.

키워드

참고문헌

  1. Alampalli, S. (1998), "Influence of in-service environment on modal parameters", Proceedings IMAC XVI-International Modal Analysis Conference, 111-116.
  2. Allemang, R.J. (2002), "The Modal Assurance Criterion (MAC): Twenty years of use and abuse", Proceedings IMAC XX- International Modal Analysis Conference.
  3. Alves, V., Cury, A. and Cremona, C. (2016), "On the use of symbolic vibration data for robust structural health monitoring", Proc. Inst. Civil Eng. Struct. Build., 169(9), 715-723. https://doi.org/10.1680/jstbu.15.00011
  4. Alves, V., Cury, A., Roitman, N., Magluta, C. and Cremona, C. (2015), "Novelty detection for SHM using raw acceleration measurements", Struct. Control Hlth. Monit., 22(9), 1193-1207. https://doi.org/10.1002/stc.1741
  5. Cardoso, R., Cury, A. and Barbosa, F. (2017), "A robust methodology for modal parameters estimation applied to SHM", Mech. Syst. Signal Pr., 95, 24-41. https://doi.org/10.1016/j.ymssp.2017.03.021
  6. Chinmaya, K. and Mohanty, A.R. (2006), "Multistage gearbox condition monitoring using motor current signature analysis and Kolgomorov-Smirnov test", J. Sound Vib., 290, 337-368. https://doi.org/10.1016/j.jsv.2005.04.020
  7. Cury, A.A., Borges, C.C.H. and Barbosa, F.S. (2011), "A two-step technique for damage assessment using numerical and experimental vibration data", Struct. Hlth. Monit., 10(4), 417-428. https://doi.org/10.1177/1475921710379513
  8. Farrar, C.R. and Worden, K. (2013), Structural Health Monitoring: A Machine Learning Perspective, John Wiley & Sons.
  9. Farrar, C.R., Baker, W.E., Bell, T.M., Cone, K.M., Darling, T.W., Duffey, T.A., ... and Migliori, A. (1994). "Dynamic characterization and damage detection in the I-40 bridge over the Rio Grande (No. LA--12767-MS)", Los Alamos National Lab., NM, USA.
  10. Farrar, C.R., Doebling, S.W., Cornwell, P.J. and Straser, E.G. (1997), "Variability of modal parameters measured on the Alamosa Canyon Bridge", Proceedings IMAC XV-International Modal Analysis Conference.
  11. Gentile C., Guidobaldi, M. and Saisi, A. (2016), "One-year dynamic monitoring of a historic tower: damage detection under changing environment", Meccanica, 51(11), 2873-2889. https://doi.org/10.1007/s11012-016-0482-3
  12. Hastie (2009), The Elements of Statistical Learning: Data Mining, Inference and Prediction, 2nd Edition, Palo Alto, California: Springer.
  13. Mathwoks Inc. (2015), "Kolmogorov test/Documentation Center/ Statistical Toolbox", http://www.mathworks.com.
  14. Meruane, V. and Heylen, W. (2012), "Structural damage assessment under varying temperature conditions", Struct. Hlth. Monit., 11, 345-357. https://doi.org/10.1177/1475921711419995
  15. Nguyen, V.H., Mahowald, J., Golinval, J.C. and Maas, S. (2014), "Damage detection in bridge structures including environmental effects", Proceedings of the 9th International Conference on Structural Dynamics, EURODYN.
  16. Oakland, J. (2007), Statistical Process Control, 6th Edition, Routledge.
  17. Ortiz Morales, F.A. (2016), "Avaliacao da influencia da temperatura sobre os parametros modais de estruturas", Dissertacao de mestrado. Universidade Federal de Ouro Preto, Ouro Preto.
  18. Peeters, B. and De Roeck, G. (2001), "One-year monitoring of the Z-24 Bridge: Environmental effects vs damage events", Earthq. Eng. Struct. Dyn., 30, 149-171. https://doi.org/10.1002/1096-9845(200102)30:2<149::AID-EQE1>3.0.CO;2-Z
  19. Poh, W. (2001), "Stress-strain-temperature relationship for structural steel", J. Mater. Civil Eng., 13(5), 371-379. https://doi.org/10.1061/(ASCE)0899-1561(2001)13:5(371)
  20. Rohrmann, R.G., Baessler, M., Said, S. and Schmid, W. (2000), "Structural causes of temperature affected modal data of civil structures obtained by long time monitoring", Proceedings IMAC XVIII-International Modal Analysis Conference, 1-7.
  21. Saisi, A., Gentile, C. and Guidobaldi, M. (2015), "Post-earthquake continuous dynamic monitoring of the Gabbia Tower in Mantua, Italy", Constr. Build. Mater., 81, 101-112. https://doi.org/10.1016/j.conbuildmat.2015.02.010
  22. Sohn, H., Dzwonczyk, M., Straser, E.G., Kiremidjian, A.S., Law, K.H. and Meng, T. (1999), "An experimental study of temperature effect on modal parameters of the Alamosa Canyon Bridge", Earthq. Eng. Struct. Dyn., 28, 879-897. https://doi.org/10.1002/(SICI)1096-9845(199908)28:8<879::AID-EQE845>3.0.CO;2-V
  23. Soon, 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", Report LA13976MS, 1996-2001.
  24. Vimal Mohan, S., Parivallal, K., Kesavan, B., Arunsundaram, A., Farvaze Ahmed, K. and Ravisankar, K. (2014), "Studies on damage detection using frequency change correlation approach for health assessment", Procedia Eng., 86, 503-510. https://doi.org/10.1016/j.proeng.2014.11.074
  25. Wang, L., Lie, S.T. and Zhang, Y. (2016), "Damage detection using frequency shift path", Mech. Syst. Signal Pr., 66-67, 298-313. https://doi.org/10.1016/j.ymssp.2015.06.028
  26. Wasserstein, R. and Lazar, N.A. (2016), "The ASA's statement on p-values: context, process and purpose", Am. Statistic., 70(2), 129-133. https://doi.org/10.1080/00031305.2016.1154108
  27. Wei, J.J. and Lv, Z.R. (2015), "Structural damage detection including the temperature difference based on response sensitivity analysis", Struct. Eng. Mech., 53(2), 249-260. https://doi.org/10.12989/sem.2015.53.2.249
  28. 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
  29. Yan, A.M., Kerschen, G., De Boe, P. and Golinval, J.C. (2005a), "Structural damage diagnosis under varying environmental conditions-part I: A linear analysis", Mech. Syst. Signal Pr., 19, 847-864. https://doi.org/10.1016/j.ymssp.2004.12.002
  30. Yan, A.M., Kerschen, G., De Boe, P. and Golinval, J.C. (2005b), "Structural damage diagnosis under varying environmental conditions-part II: Local PCA for non-linear cases", Mech. Syst. Signal Pr., 19, 865-880. https://doi.org/10.1016/j.ymssp.2004.12.003
  31. Yu, L. and Zhu, J.H. (2015), "Nonlinear damage detection using higher statistical moments of structural responses", Struct. Eng. Mech., 54(2), 221-237. https://doi.org/10.12989/sem.2015.54.2.221