CFP last date
20 December 2024
Reseach Article

Vibration Signal Denoising using Neighbourhood and Parent-Child Relationship of Wavelet Transform Coefficients

by Pooja Yadav, Preety D. Swami
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 130 - Number 4
Year of Publication: 2015
Authors: Pooja Yadav, Preety D. Swami
10.5120/ijca2015906874

Pooja Yadav, Preety D. Swami . Vibration Signal Denoising using Neighbourhood and Parent-Child Relationship of Wavelet Transform Coefficients. International Journal of Computer Applications. 130, 4 ( November 2015), 37-42. DOI=10.5120/ijca2015906874

@article{ 10.5120/ijca2015906874,
author = { Pooja Yadav, Preety D. Swami },
title = { Vibration Signal Denoising using Neighbourhood and Parent-Child Relationship of Wavelet Transform Coefficients },
journal = { International Journal of Computer Applications },
issue_date = { November 2015 },
volume = { 130 },
number = { 4 },
month = { November },
year = { 2015 },
issn = { 0975-8887 },
pages = { 37-42 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume130/number4/23200-2015906874/ },
doi = { 10.5120/ijca2015906874 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:24:29.795062+05:30
%A Pooja Yadav
%A Preety D. Swami
%T Vibration Signal Denoising using Neighbourhood and Parent-Child Relationship of Wavelet Transform Coefficients
%J International Journal of Computer Applications
%@ 0975-8887
%V 130
%N 4
%P 37-42
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

A method based on intra-scale and inter-scale dependency of coefficient of stationary wavelet transform has been developed for vibration signal denoising. In this paper, features of Stationary Wavelet Transform are revised by comparing it to Discrete Wavelet Transform. Proposed denoising method is simulated for different noise values and results are compared to other denoising methods. Proposed method is used for treatment of practical signals to confirm that the proposed method is suitable and efficient in improving the SNR of the vibration signal and in processing the original information by retaining its shape.

References
  1. B.K.N. Rao, Handbook of Condition Monitoring, Elsevier Advanced Technology, Oxford, 1996.
  2. H. Mahguon, R.E. Bekka, and A. felkaoui, “Gearbox fault detection using a new denoising method on ensemble emphirical mde decomposition and FFT,” Mechanical System and Signal Processing, vol. 11,no. 3,pp.331-350 .
  3. . Polikar “The wavelet tutorial by Robi Polikar .” Avalable:http://users.rowan.edu/~polikar/WAVELETS/WTtutorial.html,1996.
  4. Z.K. Peng, F.I. Chu “Application of wavelet Transform in Machine Condition Monitoring and Fault Diagnostic: A review with biblography,Mech sys.Signal process 18(2004) 199-221.
  5. Yaguo Lei , Jing Lin , Zhengjia He , Ming J. Zuo , “A review on empirical ode decomposition in fault diagnosis of rotating machinery” oct.2012.
  6. J.Antonino-Daviu,M. Riera-Guasp,J. Roger-Folch, F.Martinez-Gimenez,A.peris “Application and optimization of discrete wavelet transform for detection of broken rotor bars in induction machines” March 2006.
  7. R.Rubini, and U.Meneghetti, “Application of the envelope and wavelet transform anaysis for the diagnosis of incipient faults in ball bearings,” Mechanical System and Signal Processing, vol. 15 no.2 , pp. 287-302, March 2001
  8. G.P. Nason and B.W. Silverman “ The Stationary Wavelet Transform and some Statistical Application” in: Department of Mathematics, University of Bristol, Bristol BS8 ITW , UK,1996.
  9. D.L. Donoho , Denoising by soft thresholding, IEEE transaction on information theory 41(1995) 613-627.
  10. R.R. Coifman, D.L. Donoho, Translation invariant denoising, in: wavelet and statistics,Springer Lecture Notes in Statistics Vol. 103, Springer , New York, pp. 125-150.
  11. T.T. Cai, B.W. Silverman, Incorporating information on neighbouring coefficients in wavelet estimation, Sankhya: The Indian Journal of statistics Series B 63 (Part 2) (2001) 127-150.
  12. Shweta Garde,Preety D. Swami “ Noise Reduction of Vibration Signals in Rotary Machines using Neighbourhood Correlation of Wavelet Transform Coefficient”, in: International Conference on Signal Processing, Embedded System and Commnication Technologies annd their application for Sustainable and Renewable Energy, June 2014.
  13. Li Zhen , He Zhengjia, Zi Yanyang#, Wang Yanxue# “Cutomized wavelet denoising using intra and inter scale dependency for bearing fault detection” school of mechanical engineering, Xian Jiaotong University, 710049,China, accepted 17 November 2007.
Index Terms

Computer Science
Information Sciences

Keywords

De-noising Vibration signal Wavelet Transform Parent-child relationship Neighbourhood