Table of Contents Author Guidelines Submit a Manuscript
Shock and Vibration
Volume 2018, Article ID 1590983, 10 pages
https://doi.org/10.1155/2018/1590983
Research Article

Bolt Detection Signal Analysis Method Based on ICEEMD

1College of Water Conservancy and Hydropower Engineering, Hohai University, Nanjing, China
2Key Laboratory of Hydraulic and Waterway Engineering of the Ministry of Education, Chongqing Jiaotong University, Chongqing, China
3Department of Electrical and Computer Engineering, Northeastern University, Boston, MA, USA

Correspondence should be addressed to Zhan Zhang; moc.qq@uhh_gnahznahz

Received 23 September 2017; Revised 9 January 2018; Accepted 28 February 2018; Published 18 April 2018

Academic Editor: Carlo Trigona

Copyright © 2018 Chunhui Guo et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. B. Stimpson, “A simple rock bolt pull-out test device for teaching purposes,” International Journal of Rock Mechanics and Mining Sciences, vol. 21, no. 4, pp. 217-218, 1984. View at Publisher · View at Google Scholar · View at Scopus
  2. U. G. Shuan-Cheng, J. Zhang, S. Zhang et al., “Influence Analysis of Anchoring Defects on Bolt Pull-out Load,” Safety in Coal Mines, 2013. View at Google Scholar
  3. A. Ivanović, A. Starkey, R. D. Neilson, and A. A. Rodger, “The influence of load on the frequency response of rock bolt anchorage,” Advances in Engineering Software, vol. 34, no. 11-12, pp. 697–705, 2003. View at Publisher · View at Google Scholar · View at Scopus
  4. M. D. Beard and M. J. S. Lowe, “Non-destructive testing of rock bolts using guided ultrasonic waves,” International Journal of Rock Mechanics and Mining Sciences, vol. 40, no. 4, pp. 527–536, 2003. View at Publisher · View at Google Scholar · View at Scopus
  5. H. X. Yue, G. M. Liu, and L. I. Qi, “Development of Bolt’s Testing Technique,” Soil Engineering & Foundation, 2005. View at Google Scholar
  6. S. M. Parvasi, S. C. M. Ho, Q. Kong, R. Mousavi, and G. Song, “Real time bolt preload monitoring using piezoceramic transducers and time reversal technique - A numerical study with experimental verification,” Smart Materials and Structures, vol. 25, no. 8, Article ID 085015, 2016. View at Publisher · View at Google Scholar · View at Scopus
  7. G. Song, W. Li, B. Wang, and S. C. M. Ho, “A review of rock bolt monitoring using smart sensors,” Sensors, vol. 17, no. 4, article no. 776, 2017. View at Publisher · View at Google Scholar · View at Scopus
  8. Q. J. Zhang, U. W. Ji-Min, G. Peng et al., “Factors in quality of special bolts based on sonic non-destructive detection,” Journal of Hohai University, vol. 37, no. 2, pp. 179–184, 2009. View at Google Scholar
  9. D. Zeng H and S. Wang S, “Analysis on lateral dynamic response of anchor system[J],” Chinese Journal of Underground Space Engineering, 2010. View at Google Scholar
  10. M. Rucka and B. Zima, “Elastic wave propagation for condition assessment of steel bar embedded in mortar,” International Journal of Applied Mechanics and Engineering, vol. 20, no. 1, pp. 159–170, 2015. View at Publisher · View at Google Scholar · View at Scopus
  11. G. Wang and B. Li, “Research on Non-destructive Testing Techniques of Bolt,” Chinese Journal of Engineering Geophysics, 2009. View at Google Scholar
  12. C. Wang, W. He, J. Ning, and C. Zhang, “Propagation properties of guided wave in the anchorage structure of rock bolts,” Journal of Applied Geophysics, vol. 69, no. 3-4, pp. 131–139, 2009. View at Publisher · View at Google Scholar · View at Scopus
  13. J. Wang, Y. Zhao, B. Yao, and J. Xu, “Filtering detecting signal of rockbolt with harmonic wavelet,” Mining Science and Technology, vol. 20, no. 3, pp. 411–414, 2010. View at Publisher · View at Google Scholar · View at Scopus
  14. M. I. Lee, I. S. Han, J. H. Kim et al., “Evaluation of rock bolt integrity using Fourier and wavelet transforms,” Tunnelling & Underground Space Technology Incorporating Trenchless Technology Research, vol. 28, no. 28, pp. 304–314, 2012. View at Publisher · View at Google Scholar
  15. M. Szmajda, K. Górecki, and J. Mroczka, “Gabor transform, spwvd, gabor-wigner transform and wavelet transform - tools for power quality monitoring,” Metrology and Measurement Systems, vol. 17, no. 3, p. 6, 2010. View at Google Scholar · View at Scopus
  16. J. Xu, Q. Ren, and Z. Shen, “Low strain pile testing based on synchrosqueezing wavelet transformation analysis,” Journal of Vibroengineering, vol. 18, no. 2, pp. 813–825, 2016. View at Google Scholar · View at Scopus
  17. J. Xu, Q. Ren, and Z. Shen, “1893. Ground-penetrating radar time-frequency analysis method based on synchrosqueezing wavelet transformation,” Journal of Vibroengineering, vol. 18, no. 1, pp. 315–323, 2016. View at Google Scholar · View at Scopus
  18. N. E. Huang and Z. Wu, “A review on Hilbert-Huang transform: method and its applications to geophysical studies,” Reviews of Geophysics, vol. 46, no. 2, Article ID RG2006, 2008. View at Publisher · View at Google Scholar · View at Scopus
  19. P. Flandrin, G. Rilling, and P. Gonçalvés, “Empirical mode decomposition as a filter bank,” IEEE Signal Processing Letters, vol. 11, no. 2, pp. 112–114, 2004. View at Publisher · View at Google Scholar · View at Scopus
  20. C. M. Wu and N. E. Huang, Biomedical Data Processing Using HHT: A Review, Springer, Berlin Heidelberg, Germany, 2009.
  21. A.-O. Boudraa and J.-C. Cexus, “EMD-based signal filtering,” IEEE Transactions on Instrumentation & Measurement, vol. 56, no. 6, pp. 2196–2202, 2007. View at Publisher · View at Google Scholar · View at Scopus
  22. D. Yu, J. Cheng, and Y. Yang, “Application of EMD method and Hilbert spectrum to the fault diagnosis of roller bearings,” Mechanical Systems and Signal Processing, vol. 19, no. 2, pp. 259–270, 2005. View at Publisher · View at Google Scholar · View at Scopus
  23. Y. Kopsinis and S. McLaughlin, “Development of {EMD}-based denoising methods inspired by wavelet thresholding,” IEEE Transactions on Signal Processing, vol. 57, no. 4, pp. 1351–1362, 2009. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  24. S. Z. Lin and S. G. Wang, “EMD analysis of northern hemisphere temperature variability during last 4 centuries,” Journal of Tropical Meteorology, vol. 20, no. 1, pp. 90–96, 2004. View at Google Scholar
  25. T. Wang, M. Zhang, Q. Yu, and H. Zhang, “Comparing the applications of EMD and EEMD on time-frequency analysis of seismic signal,” Journal of Applied Geophysics, vol. 83, pp. 29–34, 2012. View at Publisher · View at Google Scholar · View at Scopus
  26. C.-S. Chen and Y. Jeng, “Natural logarithm transformed EEMD instantaneous attributes of reflection data,” Journal of Applied Geophysics, vol. 95, pp. 53–65, 2013. View at Publisher · View at Google Scholar · View at Scopus
  27. Y. G. Lei, Z. J. He, and Y. Y. Zi, “EEMD method and WNN for fault diagnosis of locomotive roller bearings,” Expert Systems with Applications, vol. 38, no. 6, pp. 7334–7341, 2011. View at Publisher · View at Google Scholar · View at Scopus
  28. Z. H. Wu and N. E. Huang, “Ensemble empirical mode decomposition: a noise-assisted data analysis method,” Advances in Adaptive Data Analysis (AADA), vol. 1, no. 1, pp. 1–41, 2009. View at Publisher · View at Google Scholar · View at Scopus
  29. J. Helske and P. Luukko, “Ensemble Empirical Mode Decomposition (EEMD) and Its CompleteVariant (CEEMDAN),” International Journal of Public Health, vol. 60, no. 5, pp. 1–9, 2016. View at Google Scholar
  30. Y. Zhang and Z. Xie, “Ensemble empirical mode decomposition of impact-echo data for testing concrete structures,” NDT & E International, vol. 51, pp. 74–84, 2012. View at Publisher · View at Google Scholar · View at Scopus
  31. J. Li, C. Liu, Z. Zeng, and L. Chen, “GPR signal denoising and target extraction with the CEEMD method,” IEEE Geoscience and Remote Sensing Letters, vol. 12, no. 8, pp. 1615–1619, 2015. View at Publisher · View at Google Scholar · View at Scopus
  32. M. A. Colominas, G. Schlotthauer, and M. E. Torres, “Improved complete ensemble EMD: a suitable tool for biomedical signal processing,” Biomedical Signal Processing and Control, vol. 14, no. 1, pp. 19–29, 2014. View at Publisher · View at Google Scholar · View at Scopus
  33. W. Chen, “Ground roll attenuation using improved complete ensemble empirical mode decompoistion[J],” Journal of Seismic Exploration, p. 25, 2016. View at Google Scholar
  34. M. E. Torres, M. A. Colominas, G. Schlotthauer, and P. Flandrin, “A complete ensemble empirical mode decomposition with adaptive noise,” in Proceedings of the 36th IEEE International Conference on Acoustics, Speech, and Signal Processing, pp. 4144–4147, Prague, Czech Republic, May 2011. View at Publisher · View at Google Scholar · View at Scopus
  35. L. Gan, L. Zhou, and S. M. Liu, “A de-noising method for GPR signal based on EEMD,” Applied Mechanics and Materials, vol. 687-691, pp. 3909–3913, 2014. View at Publisher · View at Google Scholar · View at Scopus
  36. J. Xu, L. Liu, Q. Ren et al., “EEMD analysis of GPR signal in time domain,” Journal of Hefei University of Technology, vol. 35, no. 5, pp. 639–642, 2015. View at Google Scholar
  37. J. Xu, Q. Ren, and L. Huang, “GPR signal analysis method based on variational mode decomposition,” Journal of Hohai University, vol. 46, no. 1, pp. 78–85, 2018. View at Google Scholar
  38. X. An and J. Yang, “Denoising of hydropower unit vibration signal based on variational mode decomposition and approximate entropy,” Transactions of the Institute of Measurement and Control, vol. 38, no. 3, pp. 282–292, 2016. View at Publisher · View at Google Scholar · View at Scopus