DWT-Based Adaptive Filter and its Application on Canceling Noise in Mechanical Signals

Wen Tao Sui; Dan Zhang

doi:10.4028/www.scientific.net/KEM.439-440.6

Paper Titles

Committees and Sponsors

Preface

Mechanical Vibration Analysis Using ANC and Morlet Wavelet
p.1

DWT-Based Adaptive Filter and its Application on Canceling Noise in Mechanical Signals
p.6

Noise Reduction of ECG Signal Based on Morphological Filtering and WT
p.12

Distribution of Temperature Field for Rolling H-Beam
p.17

Load Distribution of Rolling Bearing for Steel Shapes Universal Roll Mill
p.23

Intrusion Detection Based on Self-Organizing Map and Artificial Immunisation Algorithm
p.29

The Performance Assessment Strategy in DC-BTA Multiple Sequence Alignment
p.35

HomeKey Engineering MaterialsKey Engineering Materials Vols. 439-440DWT-Based Adaptive Filter and its Application on...

DWT-Based Adaptive Filter and its Application on Canceling Noise in Mechanical Signals

Abstract:

A method for canceling noise in mechanical signals was presented, which was based on adaptive filtering and discrete wavelet transform Through multi-scale decomposition of wavelet transform, the isolated noise components was as the input signals of the adaptive filter. Through the simulated signal, it shows that the method can achieve noise reduction of non-stationary signals. The proposed approach for noise reduction has been successfully applied to fault diagnosis of bearing signals.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Key Engineering Materials (Volumes 439-440)

Pages:

6-11

DOI:

https://doi.org/10.4028/www.scientific.net/KEM.439-440.6

Citation:

Cite this paper

Online since:

June 2010

Authors:

Wen Tao Sui, Dan Zhang

Keywords:

Adaptive Noise Canceling (ANC), Discrete Wavelet Transform (DWT), Mechanical Signal Processing, Noise Reduction

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] H. Hong, and M. Liang : K-hybrid: a kurtosis based hybrid thresholding method for mechanical signal de-noising, ASME Trans. Journal Vibration and Acoustics, Vol. 129, No. 4, 458-470. (2007).

DOI: 10.1115/1.2748467

Google Scholar

[2] J. Wang, Q. Xiao, Y. Jiang, et al. An Adaptive Filter Model Based on Wavelet Transform. WRI Global Congress on Intelligent Systems, vol. 3, pp.136-139, 2009, (2009).

DOI: 10.1109/gcis.2009.342

Google Scholar

[3] H. Wang and P. Chen: Fault Diagnosis for a Rolling Bearing Used in a Reciprocating Machine by Adaptive Filtering Technique and Fuzzy Neural Network, WSEAS Transactions on Systems, Issue 1, Volume 7, pp.1-6. (2008).

Google Scholar

[4] Widrow, B., Glover, J.R., et al. : Adaptive noise cancelling: principles and applications, Proc. of IEEE , Vol. 63 No. 12, 1692-1716. (1975).

DOI: 10.1109/proc.1975.10036

Google Scholar

[5] K.A. Loparo, Bearings vibration data set, Case Western Reserve University, http: /www. eecs. cwru. edu/laboratory/bearing.

Google Scholar

[6] D. Zhang , W.T. Sui: The Optimal Morlet Wavelet and Its Application on Mechanical Fault Detection, Proc. of WICOM 2009, pp.518-521. (2009).

Google Scholar

[7] W.T. Sui;D. Zhang: Fault Diagnosis of Roller Bearing Conditions Using ANFIS, Applied Mechanics and Materials, Vol 16-19 , pp.886-890. (2009).

DOI: 10.4028/www.scientific.net/amm.16-19.886

Google Scholar