Application of Wavelet Transform in the De-Noising of Angular Displacement Signals of Crank Rocker Mechanism

Xiao Cun Jiang; Xiao Liu; Kui Xia Han; Ji Fang Liu; Xiao Cui

doi:10.4028/www.scientific.net/AMM.687-691.1062

Paper Titles

Application of Correlation Dimension in Extraction of Power Plant Blower Bearing Fault Feature
p.1044

The GUI-Based Simulation Optimization Platform for Fault Grey Prediction of Diesel Engine
p.1049

Research on Acoustic Mechanical Fault Diagnosis Method of High Voltage Circuit Breaker Based on Improved EEMD
p.1054

Application of Buffer Operator and Modified GM(1,1) Model to the Prediction of Gear Fatigue Life
p.1058

Application of Wavelet Transform in the De-Noising of Angular Displacement Signals of Crank Rocker Mechanism
p.1062

Design of Building Energy Consumption Monitoring Platform
p.1066

Wireless Sensor Networks to Predict the Range Covered by the Priority Scheduling Algorithm for Multi-Target Tracking
p.1071

Design of Distribute Monitoring Platform Base on Cloud Computing
p.1076

Analysis of Phased Array Antenna’s Vibration Effects on the Performance of Shipborne MLS
p.1080

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 687-691Application of Wavelet Transform in the De-Noising...

Application of Wavelet Transform in the De-Noising of Angular Displacement Signals of Crank Rocker Mechanism

Abstract:

In order to get rid of noise from the angular displacement of the crank rocker mechanism, the wavelet transform method is introduced. After the noise corresponds to the high frequency band of wavelet domain of the signal and the signal corresponds to the low frequency band of wavelet domain of the signal, the signal is decomposed into four layers, and the high frequency brand is set zero. The test results show that this method was most ideal for the de-noising effect on displacement signals, which is able to not only retain valid signals but to effectively remove the noise.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volumes 687-691)

Pages:

1062-1065

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.687-691.1062

Citation:

Cite this paper

Online since:

November 2014

Authors:

Xiao Cun Jiang*, Xiao Liu, Kui Xia Han, Ji Fang Liu, Xiao Cui

Keywords:

Angular Displacement, Angular Velocity, Crank Rocker Mechanism, De-Noising, Wavelet Transform (WT)

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

* - Corresponding Author

References

[1] Chen, J., et al., Construction of customized redundant multiwavelet via increasing multiplicity for fault detection of rotating machinery. Mechanical Systems and Signal Processing, 2014. 42(1): pp.206-224.

DOI: 10.1016/j.ymssp.2013.08.024

Google Scholar

[2] Solís, M., M. Algaba and P. Galvín, Continuous wavelet analysis of mode shapes differences for damage detection. Mechanical Systems and Signal Processing, 2013. 40(2): pp.645-666.

DOI: 10.1016/j.ymssp.2013.06.006

Google Scholar

[3] Klepka, A. and T. Uhl, Identification of modal parameters of non-stationary systems with the use of wavelet based adaptive filtering. Mechanical Systems and Signal Processing, (2013).

DOI: 10.1016/j.ymssp.2013.09.001

Google Scholar

[4] Yan, G., et al., Structural damage detection using residual forces based on wavelet transform. Mechanical Systems and Signal Processing, 2010. 24(1): pp.224-239.

DOI: 10.1016/j.ymssp.2009.05.013

Google Scholar

[5] Wang, Y., Z. He and Y. Zi, Enhancement of signal denoising and multiple fault signatures detecting in rotating machinery using dual-tree complex wavelet transform. Mechanical Systems and Signal Processing, 2010. 24(1): pp.119-137.

DOI: 10.1016/j.ymssp.2009.06.015

Google Scholar

[6] Bayissa, W.L., N. Haritos and S. Thelandersson, Vibration-based structural damage identification using wavelet transform. Mechanical Systems and Signal Processing, 2008. 22(5): pp.1194-1215.

DOI: 10.1016/j.ymssp.2007.11.001

Google Scholar

[7] Zhong, S. and S.O. Oyadiji, Crack detection in simply supported beams without baseline modal parameters by stationary wavelet transform. Mechanical Systems and Signal Processing, 2007. 21(4): pp.1853-1884.

DOI: 10.1016/j.ymssp.2006.07.007

Google Scholar

[8] Schukin, E.L., R.U. Zamaraev and L.I. Schukin, The optimisation of wavelet transform for the impulse analysis in vibration signals. Mechanical systems and signal processing, 2004. 18(6): pp.1315-1333.

DOI: 10.1016/j.ymssp.2004.01.008

Google Scholar