Smart Structures and Systems

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Local damage detection of a fan blade under ambient excitation by three-dimensional digital image correlation

  • Hu, Yujia (School of Mechanical Engineering, University of Shanghai for Science and Technology) ;
  • Sun, Xi (School of Mechanical Engineering, University of Shanghai for Science and Technology) ;
  • Zhu, Weidong (2Department of Mechanical Engineering, University of Maryland) ;
  • Li, Haolin (School of Mechanical Engineering, University of Shanghai for Science and Technology)
  • Received : 2019.06.13
  • Accepted : 2019.08.16
  • Published : 2019.11.25
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Abstract

Damage detection based on dynamic characteristics of a structure is one of important roles in structural damage identification. It is difficult to detect local structural damage using traditional dynamic experimental methods due to a limited number of sensors used in an experiment. In this work, a non-contact test stand of fan blades is established, and a full-field noncontact test method, combined with three-dimensional digital image correlation, Bayesian operational modal analysis, and damage indices, is used to detect local damage of a fan blade under ambient excitation without use of baseline information before structural damage. The methodology is applied to detect invisible local damage on the fan blade. Such a method has a seemingly high potential as an alternative to detect local damage of blades with complex high-precision surfaces under extreme working conditions because it is a noncontact test method and can be used under ambient excitation without human participation.

Keywords

Acknowledgement

Supported by : Shanghai Natural Science Foundation, Shanghai Science and Technology Innovation Fund, National Science Foundation, National Natural Science Foundation of China

References

  1. Au, S.K. (2011), "Fast bayesian FFT method for ambient modal identification with separated modes", J. Eng. Mech., 137, 214-226. DOI: 10.1061/(ASCE)EM.1943-7889.0000213.
  2. Au, S.K., Zhang, F.L. and Ni, Y.C. (2013), "Bayesian operational modal analysis: theory, computation, practice", Comput. Struct., 126, 3-14. DOI: 10.1016/j.compstruc.2012.12.015.
  3. Beberniss, T.J. and Ehrhardt, D.A. (2016), "High-speed 3D digital image correlation vibration measurement: recent advancements and noted limitations", Mech. Syst. Signal Pr., 86, 35-48. DOI: 10.1016/j.ymssp.2016.04.014.
  4. Brownjohn, J., Au, S., Zhu, Y., Sun, Z., Li, B., Bassitt, J., Hudson, E. and Sun, H. (2018), "Bayesian operational modal analysis of Jiangyin Yangtze River bridge", Mech. Syst. Signal Pr., 110, 210-230. DOI: 10.1016/j.ymssp.2018.03.027.
  5. Bruck, H.A., McNeill, S.R., Sutton, M.A. and Peters, W.H. (1989), "Digital image correlation using newton-raphson method of partial differential correction", Exp. Mech., 29(3), 261-267. DOI: 10.1007/BF02321405.
  6. Cawley, P. and Admas, R.D. (1979), "The location of defects in structures from measurements of the natural frequencies", J. Strain Anal., 14(2), 49-57. DOI: 10.1243/03093247V142049.
  7. Chevalier, L., Calloch, S., Hild, F. and Marco, Y. (2001), "Digital image correlation used to analyze the multiaxial behavior of rubber-like materials", Eur. J. Mech. A-Solids., 20(1), 169-187. DOI: 10.1016/S0997-7538(00)01135-9.
  8. Feng, Z. and Rowlands, R.E. (1987), "Continuous full-field representation and differentiation of three-dimensional experimental vector data", Comput. Struct., 26(6), 979-990. DOI: 10.1016/0045-7949(87)90115-5.
  9. Ha, N.S., Vang, H.M. and Goo, N.S. (2015), "Modal analysis using digital image correlation technique: An application to artificial wing mimicking beetle's hind wing", Exp. Mech., 55(5), 989-998. DOI: 10.1007/s11340-015-9987-2.
  10. Hagara, M., Trebuna, F., Hunady, R. and Kalina, M. (2012), "Experimental identification of modal parameters of thin metal sheets by using of DIC", Procedia Eng., 48(1), 180-188. DOI: 10.1016/j.proeng.2012.09.503.
  11. Hartley, R. and Zisserman, A. (2003), Multiple View Geometry in Computer Vision, Cambridge University Press, Cambridge, UK
  12. Helfrick, M. N., Niezrecki, C., Avitabile, P. and Schmidt, T. (2011), "3D digital image correlation methods for full-field vibration measurement", Mech. Syst. Signal Pr., 25(3), 917-927. DOI: 10.1016/j.ymssp.2010.08.013.
  13. Hu, Y.J., Guo, W.G., Jiang, C. and Zhou Y.L. and Zhu, W.D. (2018), "Looseness localization for bolted joints using Bayesian operational modal analysis and modal strain energy", Adv. Mech. Eng., 10, 1-10. DOI: 10.1177/1687814018808698.
  14. Hu, Y.J., Guo, W.G., Zhu, W.D. and Xu, Y. (2019), "Local damage detection of membranes based on Bayesian operational modal analysis and three-dimensional digital image correlation", Mech. Syst. Signal Pr., 131, 633-648. DOI: 10.1016/j.ymssp.2019.04.051.
  15. Hu, Y.J., Jiang, C., Liu, W., Yu, Q.Q. and Zhou, Y.L. (2018c), "Degradation of the in-plane shear modulus of structural BFRP laminates due to high temperature", Sensors, 18(10), 1-16. DOI: 10.3390/s18103361.
  16. Hu, Y.J., Liu, F., Zhu, W.D. and Zhu, J.M. (2018a), "Thermally coupled constitutive relations of thermoelastic materials and determination of their material constants based on digital image correlation with a laser engraved speckle pattern", Mech. Mater., 120, 26-36. DOI: 10.1016/j.mechmat.2018.02.002.
  17. Hu, Y.J., Wang, Y.J., Chen, J.B. and Zhu, J.M. (2018b), "A new method of creating high-temperature speckle patterns and its application in the determination of the high-temperature mechanical properties of metals", Exp Tech., 42, 523-532. DOI:10.1007/s40799-018-0256-z.
  18. Katafygiotis, L.S. and Yuen, K.V. (2001), "Bayesian spectral density approach for modal updating using ambient data", Earthq. Eng. Struct. D., 30(8), 1103-1123. DOI: 10.1016/S0266-8920(01)00004-2.
  19. Luo, P.F., Chao, Y.J. and Sutton, M.A. (1994), "Application of stereo vision to three-dimensional deformation analyses in fracture experiments", Opt. Eng., 33(3), 981-991. DOI: 10.1117/12.160877.
  20. Pandey, A.K., Biswas, M. and Samman, M.M. (1991), "Damage detection from changes in curvature mode shapes", J. Sound Vib., 145(2), 321-332. DOI: 10.1016/0022-460X(91)90595-B.
  21. Poozesh, P., Baqersad, J., Niezrecki, C. and Avitabile, P. (2016), "A multi-camera stereo DIC system for extracting operating mode shapes of large scale structures", Conf. Proc. Soc. Exp. Mech. Ser., 3, 225-238. DOI: 10.1007/978-3-319-22446-6_29.
  22. Schmidt, T.E., Tyson, J. and Galanulis, K. (2006), "Full-field dynamic displacement and strain measurement using advanced 3D image correlation photogrammetry: Part I", Exp. Mech., 27(3), 47-50. DOI: 10.1111/j.1747-1567.2003.tb00118.x.
  23. Shi, Z.Y., Law, S.S. and Zhang, L.M. (1998), "Structural damage localization from modal strain energy change", J. Sound Vib., 218(5), 825-844. DOI: 10.1006/jsvi.1998.1878.
  24. Sutton, M.A. (1991), "Full-field representation of discretely sampled surface deformation for displacement and strain analysis", Exp. Mech., 31(2), 168-177. DOI: 10.1007/BF02327571.
  25. Wang, C.C., Deng, J.M., Ateshian, G.A. and Hung, C.T. (2002), "An automated approach for direct measurement of two-dimensional strain distributions within articular cartilage under unconfined compression", J. Biomech. Eng., 124(5), 557-567. DOI: 10.1115/1.1503795.
  26. Xu, Y.F. and Zhu, W.D. (2017), "Non-model-based damage identification of plates using measured mode shapes", Struct. Health Monit., 16(1), 3-23. DOI: 10.1016/j.jsv.2017.03.030.
  27. Xu, Y.F., Zhu, W.D. and Smith, S.A. (2017), "Non-model-based damage identification of plates using principal, mean and Gaussian curvature mode shapes", J. Sound Vib., 400, 626-659. DOI: 10.1016/j.jsv.2017.03.030.
  28. Ye, X.W., Dong, C.Z. and Liu, T. (2016), "Image-based structural dynamic displacement measurement using different multi-object tracking algorithms", Smart Struct. Syst., 17(6), 935-956. http://dx.doi.org/10.12989/sss.2016.17.6.935.
  29. Ye, X.W., Ni, Y.Q., Wai, T.T., Wong, K.Y., Zhang, X.M. and Xu, F. (2013), "A vision-based system for dynamic displacement measurement of long-span bridges: algorithm and verification", Smart Struct. Syst., 12(3-4), 363-379. http://dx.doi.org/10.12989/sss.2013.12.3_4.363.
  30. Ye, X.W., Yi, T.H., Wen, C. and Su, Y.H. (2015), "Reliability-based assessment of steel bridge deck using a mesh-insensitive structural stress method", Smart Struct Syst., 16(2), 367-382. http://dx.doi.org/10.12989/sss.2015.16.2.367.
  31. Yuen, K.V. and Katafygiotis, L,S. (2003), "Bayesian fast Fourier transform approach for modal updating using ambient data", Adv. Struct. Eng., 6(2), 81-95. DOI: 10.1260/136943303769013183.
  32. Yuen, K.V. and Katafygiotis, L.S. (2001), "Bayesian time-domain approach for modal updating using ambient data", Probab. Eng. Eng. Mech., 16(3), 219-231. DOI: 10.1016/S0266-8920(01)00004-2.
  33. Yuen, K.V. and Katafygiotis, L.S. (2005), "Model updating using noisy response measurements without knowledge of the input spectrum", Earthq. Eng. Struct D., 34(2), 167-187. DOI: 10.1002/eqe.415.
  34. Zanarini, A. (2018), "Broad frequency band full field measurements for advanced applications: Point-wise comparisons between optical technologies", Mech. Syst. Signal Pr., 98, 968-999. DOI: 10.1016/j.ymssp.2017.05.035.