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CFRP damage identification system based on FBG sensors and ELM method

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Abstract

The identification of the damage state of Carbon fiber-reinforced plastic (CFRP) structure is the necessary information for ensuring the safety of CFRP structure. In this paper, the structural damage identification system using fiber Bragg grating (FBG) sensors and the damage identification method were investigated. FBG sensors were used to detect the structural dynamic response signal, which was generated by an active actuation way. Fourier transform and principal component analysis (PCA) were used to extract the damage characteristic. After that, the structural damage identification model was constructed based on extreme learning machine (ELM), whose input is the damage characteristic and output is the damage state. Finally, the damage identification system was established and verified on a CFRP plate with 160 mm\(\,\times\)160 mm experiment area. The experimental results showed that the identification accuracy was more than 90 %. This paper provided a reliable method for CFRP structural damage identification.

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References

  1. J. Frieden, J. Cugnoni, J. Botsis, T. Gmr, Compos. Struct. 94, 593 (2012)

    Article  Google Scholar 

  2. W.J. Staszewski, S. Mahzan, R. Traynor, Compos. Sci. Technol. 69, 1678 (2009)

    Article  Google Scholar 

  3. I.G. Kim, H.Y. Lee, J.W. Kim, J. Intel. Mat. Syst. Str. 16, 1007 (2005)

    Article  Google Scholar 

  4. M.T.H. Sultan, K. Worden, S.G. Pierce, D. Hickey, W.J. Staszewski, J.M. Dulieu-Barton, A. Hodzic, Mech. Syst. Signal. Pr. 25, 3135 (2011)

    Article  Google Scholar 

  5. S. Takeda, S. Minakuchi, Y. Okabe, N. Takeda, Compos. Part. A. Appl. S. 36, 903 (2005)

    Article  Google Scholar 

  6. B.W. Jang, Y.G. Lee, J.H. Kim, Y.Y. Kim, C.G. Kim, Struct. Control. Health. Monit. 19, 580 (2012)

    Article  Google Scholar 

  7. G. Lu, D. Liang, Y. Xu, Compos. Part. B. Eng. 43, 594 (2012)

    Article  Google Scholar 

  8. P. Capoluongo, C. Ambrosino, S. Campopiano, A. Cutolo, M. Giordano, I. Bovio, L. Lecce, A. Cusano, Sensor. Actuat. A. Phys. 133, 415 (2007)

    Article  Google Scholar 

  9. M.A. Pérez, L. Gil, S. Oller, Compos. Struct. 108, 267 (2014)

    Article  Google Scholar 

  10. P. Selva, O. Cherrier, V. Budinger, F. Lachaud, J. Morlier, Eng. Struct. 56, 794 (2013)

    Article  Google Scholar 

  11. S. Lu, M. Jiang, Q. Sui, Y. Sai, Y. Cao, F. Zhang, L. Jia, Chinese. J. Lasers. 41, 0305006 (2014). [in Chinese]

    Article  Google Scholar 

  12. T.H. Loutas, A. Panopoulou, D. Roulias, V. Kostopoulos, Expert. Syst. Appl. 39, 8412 (2012)

    Article  Google Scholar 

  13. G. Huang, H. Zhou, X. Ding, R. Zhang, T. Lee, Syst. Man. Cy. B. 42, 513 (2012)

    Article  Google Scholar 

  14. G. Huang, D. Wang, Y. Lan, Int. J. Mach. Learn. Cybern. 2, 107 (2011)

    Article  Google Scholar 

  15. J.H. Park, J.T. Kim, D.S. Hong, D.D. Ho, J.H. Yi, J. Sound. Vib. 323, 451 (2009)

    Article  ADS  Google Scholar 

  16. W. Huang, H. Yin, Image. Vis. Comput. 30, 355 (2012)

    Article  MathSciNet  Google Scholar 

  17. J. Martínez, C. Iglesias, J.M. Matías, J. Taboada, M. Araújo, Appl. Math. Comput. 69, 1678 (2009)

    Google Scholar 

Download references

Acknowledgments

This research was supported by the National Natural Science Foundation of China (No. 61174018), Natural Science Foundation of Shandong Province of China (No. ZR2011FQ025) and Fundamental research funds of Shandong University, China (Grant no. 2014YQ009).

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Correspondence to Mingshun Jiang.

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Lu, S., Jiang, M., Jia, L. et al. CFRP damage identification system based on FBG sensors and ELM method. Opt Rev 22, 46–51 (2015). https://doi.org/10.1007/s10043-015-0049-x

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  • DOI: https://doi.org/10.1007/s10043-015-0049-x

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