Call for Paper - November 2022 Edition
IJCA solicits original research papers for the November 2022 Edition. Last date of manuscript submission is October 20, 2022. Read More

Filtering of Seawall GPR Signal by means of Multi-Wavelet Transform

Print
PDF
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2019
Authors:
Jun Chen, Dingkai Chen, Shuangcheng Ge
10.5120/ijca2019919255

Jun Chen, Dingkai Chen and Shuangcheng Ge. Filtering of Seawall GPR Signal by means of Multi-Wavelet Transform. International Journal of Computer Applications 178(38):13-18, August 2019. BibTeX

@article{10.5120/ijca2019919255,
	author = {Jun Chen and Dingkai Chen and Shuangcheng Ge},
	title = {Filtering of Seawall GPR Signal by means of Multi-Wavelet Transform},
	journal = {International Journal of Computer Applications},
	issue_date = {August 2019},
	volume = {178},
	number = {38},
	month = {Aug},
	year = {2019},
	issn = {0975-8887},
	pages = {13-18},
	numpages = {6},
	url = {http://www.ijcaonline.org/archives/volume178/number38/30784-2019919255},
	doi = {10.5120/ijca2019919255},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

Background noise is and will always be an issue accompanying any type of ground-penetrating-radar (GPR) data acquisition and processing. Filtering is sometimes important for GPR data interpretation. In this paper, the principle and the characteristic of a multi-wavelet filter are presented briefly. And then the steps required to filter a GPR signal using a multi-wavelet filter are presented. The image changes of two theoretical models from the forward-calculated image to that of mixed with noise and that processed using a multi-wavelet-filter show that a multi-wavelet filter can be an effective tool for GPR signal filtering. As an example the field GPR signals of a seawall exhibiting water leakage were processed using a multi-wavelet transform. And the processed result is interpreted. The interpreted result facilitated the smooth completion of seawall waterproofing treatment.

References

  1. Baili, J., Lahouar, S., Hergli, M., et al. 2009. GPR signal de-noising by discrete wavelet transform. NDT&E International. (42): 696–703.
  2. Li, J., Guo, C. C., Wang, F. M., et al. 2007. The summary of the surface ground penetrating radar applied in subsurface investigation. Progress in Geophysics (in Chinese). 22(2): 629-637.
  3. Feng, D. S. and Dai, Q. W. 2008. The migration of GPR three dimension wave equation in wavelets domain. Chinese journal of geophysics (in Chinese). 51( 2): 566-574.
  4. Feng, D. W. and Dai, Q. W. 2009. Ground penetrating radar inverse migration processing based on multi-resolution of wavelet. Journal of Tongji University (natural science) ( in Chinese). 37(4):56564.
  5. Ye, A. W. and Xie, H. C. 2008. The application of two-dimension small wave transform in managing the ground detecting radar image. Shanxi Architecture (in Chinese). 34(13):23-24.
  6. Chen, X. P. and Cao, S. Y. 2005. GHM-like orthogonal multi-wavelet transform and its application to de-noising of seismic data. Seismology and Geology (in Chinese). 27(3): 479-486.
  7. Shi, X. M., Zhang, J., Liu, M. H., et al. 2008. Application of wavelet transform in de-nosing ground penetrating radar data. Chinese Journal of Engineering Geophysics (in Chinese). 5(3):279-286.
  8. Lehmann, F., Boemer, D. E. and olliger, K. H. 2000. Multi-component geo-radar data: Some important implications for data acquisition and processing. Geophysics, Bol. 65( 5):1542-1552.
  9. Chui, C. K. and Lian, J. A. 1996. A study of orthonoral multi-wavelets. Applied Numerical Mathematics. (20):273-298.
  10. Jiang, Q. T. 1998. Orthogonal multi-wavelets with optimum time-frequency resolution. Signal processing IEEE transactions on. (46):830-844.
  11. Cheng, Z. X., Yang, S. Z. and Zhang, L. L. 2001. The study and evolution of the theory of multi waveletes. Journal of engineering mathematics (in Chinese). 18( 5):1-16.
  12. Sun, H.L., He, Z. J. and Zi, Y. Y. 2014. et al. Multiwavelet transform and its applications in mechanical fault diagnosis - A reviews. Mechanical Systems and Signal Processing. 43:1-24.
  13. Warren, C., Giannopoulos, A. and Giannakis, I. 2016. gprMax: open source software to simulate electromagnetic wave propagation for Ground Penetrating Radar. Computer Physics Communications. 209:163-170.

Keywords

Ground-penetrating radar (GPR); multi-wavelet transformation; filter; noise reduction, signal processing