Seismic Noise Removal and its Applications – A Review of Exploring Wavelet Transform in Civil Engineering
International Journal of Civil Engineering |
© 2017 by SSRG - IJCE Journal |
Volume 4 Issue 12 |
Year of Publication : 2017 |
Authors : Sheena A D |
How to Cite?
Sheena A D, "Seismic Noise Removal and its Applications – A Review of Exploring Wavelet Transform in Civil Engineering," SSRG International Journal of Civil Engineering, vol. 4, no. 12, pp. 1-6, 2017. Crossref, https://doi.org/10.14445/23488352/IJCE-V4I12P101
Abstract:
The purpose of this study is to provide a guideline for the effective selection of wavelet type in Civil Engineering applications. Seismic denoising is the process of removing noises, ie., the unwanted disturbances present in seismic waves are removed. In seismic exploration, seismic signals are affected by a variety of interference, disturbance and noises, its related seismic data resolution to be reduced. Therefore, denoising is necessary in terms of seismic data processing, so explained in this paper.
Keywords:
Seismic Waves, Seismic Noises, Fourier Transform, Wavelet Transform, Application.
References:
[1] Alireza Golestani , S.Mahdi S.Kolbadi, Ali Akbar Heshmati(2013), “Localization and de-noising seismic signals on SASW measurement by wavelet transform” © ELSEVIER.
[2] Anooshiravan Ansari, Asadollah Noorzad b, Hamid Zafarani a, Hessam Vahidifard (2010), “Correction of highly noisy strong motion records using a modified wavelet de-noising method” © ELSEVIER.
[3] Beena mola M., J. Mohanalinb, S. Prabavathyc, Jordina Torrents-Barrenad, Domenec Puigd (2016), “A novel wavelet seismic denoising method using type Fuzzy” © ELSEVIER.
[4] Burhan Ergen, Fırat University-Turkey, “Signal and Image Denoising Using Wavelet Transform.”
[5] Byungil Kim, Hoyoung Jeong, Hyoungkwan Kim, and Bin Han, “Exploring Wavelet Applications in Civil Engineering.”
[6] Byungil Kim, Hoyoung Jeong, Hyoungkwan Kim, and Bin Han., 2017. Exploring Wavelet Applications in Civil Engineering. Construction Management. KSCE Journal of Civil Engineering, 21: 1076–1086.
[7] Chandrika Saxena, Prof. Deepak Kourav (2014),“Noises and Image Denoising Techniques: A Brief Survey” © IJETAE.
[8] G. Corso, P.S. Kuhn, L.S. Lucena, Z.D. Thome ( 2001),“Seismic ground roll time–frequency filtering using the gaussian wavelet transform” © ELSEVIER.
[9] G.Ghodrati Amiri and A.Asadii., (2009). Structural Damage Detection in plates using wavelet transform, 415-432.
[10] Hansang Kim, Hani Melhem (2003), “Damage detection of structures by wavelet analysis” © ELSEVIER.
[11] Jianwei Ma, Gerlind Plonka, Herve Chauris, “A new sparse representation of seismic data using adaptive easy-path wavelet transform.”
[12] Rongfeng Zhang and Daniel Trad - University of British Columbia, Geophysics (2002), “Noise Attenuation: A Hybrid Approach Based on Wavelet Transform.”
[13] W.G. Weng, W.C. Fan, G.X. Liao, J. Qin (2001), “Wavelet-based image denoising in (digital) particle image velocimetry” © ELSEVIER.
[14] Xue, Y.J., J.X. Cao, R.F. Tian, H.K. Du and Y.X. Shu., 2014. Application of the empirical mode decomposition and wavelet transform to seismic reflection frequency attenuation analysis, J. Petrol. Sci. Eng., 122, 360-370.
[15] Yi, T.H., H.N. Li and X.Y. Zhao.,2012. Noise smoothing for structural vibration test signals using an improved wavelet thresholding technique, Sensors, 12, 11205-11220.