Comparative Study of Vibration Signal Using Wavelet Transform

Authors(2) :-Ayubkhan N. Mulani, Sangita N. Gujar

Scientists have developed mathematical methods to imitate the processing performed by our body and extract the frequency information contained in a signal. These mathematical algorithms are called transforms and the most popular among them is the Fourier Transform. The method to analyze non-stationary signals is to first filter different frequency bands, cut these bands into slices in time, and then analyze them. The wavelet transform uses this approach. The wavelet transform or wavelet analysis is probably the most recent solution to overcome the shortcomings of the Fourier transform. In wavelet analysis the use of a fully scalable modulated window solves the signal-cutting problem. The window is shifted along the signal and for every position the spectrum is calculated. Then this process is repeated many times with a slightly shorter (or longer) window for every new cycle.

Authors and Affiliations

Ayubkhan N. Mulani
Assistant Professor, P K Technical Campus Chakan, Pune, Maharashtra, India
Sangita N. Gujar
Assistant Professor, P K Technical Campus Chakan, Pune, Maharashtra, India

Vibration Analysis, Spectral Analysis, Wavelet Transform Vibration Signal.

  1. T. Ranchin and L. Wald, "Fusion of high spatial and spectral Resolution images: The arsis concept and its implementation,'  Photogramm. Eng. Remote Sensing, vol. 66, pp. 49-61, 2000.
  2. Soma sekhar. A, Giri Prasad M. N, (2011) 'Novel approach of image fusion on MR and CT images using wavelet transforms' IEEE.
  3. Ligia Chiorean, Mircea-Florin Vaida, (2009) 'Medical image fusion based on Discrete wavelet transforms using java technology', Proceedings of the ITI 2009 31st Int. Conf. on Information Technology Interfaces, June 22-25, Cavtat, Croatia
  4. Piotr porwik, Agnieszka lisowska, (2004) 'The Haar-wavelet transform in digital image processing'.
  5. Susmitha Vekkot, and Pinkham Shukla, (2009) 'A Novel architecture for wavelet based image fusion'World academy of science, engineering and technology.
  6. Shen, jiachen ma, and Liyong ma Harbin, (2006) 'An Adaptive pixel-weighted image fusion algorithm based on Local priority for CT and MR images, IEEE
  7. William f. Herrington, Berthoid k.p. Horn, and lchiro masaki, (2005) 'Application of the discrete Haar wavelet transform to image fusion for night-time driving 'IEEE.
  8. Mohamed I. Mahmud, Moawad I. M. Dessouky, Salah Deyab, and Fatma h. Elfouly, (2007) 'Comparison between haar and daubechies wavelet transforms on FPGA technology 'world academy of science, engineering and technology.
  9. M. Aguilar and A. L. Garrett, "Neurophysiologically-motivated sensor fusion for visualization and characterization of medical imagery,' presented  at the Fusion 2001, Montreal, QC, Canada.
  10. Y.Wang and B. Lohmann, "Multisensor image fusion: Concept, method, and applications,' Univ. Bremen, Bremen, Germany, Tech. Rep., 2000.Mechatronics-Vol. 1-pp616-624.

Publication Details

Published in : Volume 3 | Issue 8 | November-December 2017
Date of Publication : 2017-12-31
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 878-883
Manuscript Number : IJSRSET1738245
Publisher : Technoscience Academy

Print ISSN : 2395-1990, Online ISSN : 2394-4099

Cite This Article :

Ayubkhan N. Mulani, Sangita N. Gujar, " Comparative Study of Vibration Signal Using Wavelet Transform , International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 3, Issue 8, pp.878-883, November-December-2017.
Journal URL : http://ijsrset.com/IJSRSET1738245

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