For Libraries For Publication Open Access Downloads About Us Contact Us
Paper Titles
Periodic Solutions for Higher Order Delay Differential Equation
p.2801
Conjugate Duality for Set-Valued Optimization of Benson Efficiency
p.2805
A New Threshold Scheme Based on Hierarchical and Sequential Share
p.2813
Design and Realization about Virtual Experiment to Mensurate Airfoil Pressure Distribution
p.2818
Engineering Surface Analysis by Bidimensional Empirical Mode Decomposition
p.2823
Schemes Selection of Yarn Tension Detection and Control Based on Fuzzy Multiple Attribute Group Decision Making
p.2829
A New Fast Combination Method of Conflict Evidences Based on Model Modification
p.2835
An Adaptive Algorithm for Forest Fire Spread Based on Genetic Algorithm
p.2842
Application of Elman Neural Networks to Predict Truck’s Operating Speed
p.2846

Engineering Surface Analysis by Bidimensional Empirical Mode Decomposition

Article Preview

Abstract:

It is well known that an engineering surface is composed of a large number of wavelengths of roughness that are superimposed on each other. Because these multi-scale features are related to different aspects of the processes the surface has undergone and closely related to the friction and wear properties of a surface, the analysis and characterization of these features becomes an important aspect of manufacture. The challenge is how to use them for acquiring knowledge and for aid to analysis. In this paper, a method for surface topography analysis is proposed based on bidimensional empirical mode decomposition (BEMD), which can provide good adaptive separation of surface texture into multiple hierarchical components known as bidimensional intrinsic mode functions (BIMFs). Applications are conducted by using a simulated surfaces to demonstrate the feasibility and applicability of using the bidimensional empirical mode decomposition method in the analysis of engineering surfaces.

You might also be interested in these eBooks
Manufacturing Process and Equipment View Preview

Info:

Periodical:

Advanced Materials Research (Volumes 694-697)

Pages:

2823-2828

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.694-697.2823

Citation:

Cite this paper

Online since:

May 2013

Authors:

Zheng Kai Zhang, Li Chen Gu, Yong Sheng Zhu

Keywords:

Adaptive Decomposition, Bidimensional Empirical Mode Decomposition, Surface Topography

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

© 2013 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

References

[1] Raja J, Muralikrishnan B, Fu S: Precis Eng, Vol. 26 (2002), p.222.

Google Scholar

[2] Liu X, Raja J:. Proceedings of the SPIE, Vol. 2825 (1996).

Google Scholar

[3] Michael D, et al: Wear, Vol.264 (2008), p.411.

Google Scholar

[4] X.Q. Jiang, L. Blunt, K.J. Stout: Precis Eng, Vol.25 (2001), p.83.

Google Scholar

[5] Huang N.E, et al: Proceedings of the Royal Society of London, Vol.454 (1998), p.903.

Google Scholar

[6] R. Chen:ADV MAT RES, Vol.211(2011),p.1031.

Google Scholar

[7] S.Y. Li, Y.C. Liu, R.B. Zhu, et al: ADV MAT RES, Vol.34(2010), p.1058.

Google Scholar

[8] Hassan.H.H, Peirce. J.W: SCEG.Vol.1(2008),p.25.

Google Scholar

[9] J. C. Nunes,et al: Image Vision Compu, vol. 21(2003), p.1019.

Google Scholar

[10] Sharif M. A. Bhuiyan, etc: EURASIP Journal on Advances in Signal Processing, 2008

DOI: 10.1155/2008/728356

Google Scholar

[11] Hardy, R.L: J Geophys Res, Vol. 76 (1971), p.1905.

Google Scholar

[12] Hardy, R.L: Comput Math Appl, Vol.19 (1990), p.163.

Google Scholar

© 2025 Trans Tech Publications Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies. For open access content, terms of the Creative Commons licensing CC-BY are applied.
Scientific.Net is a registered trademark of Trans Tech Publications Ltd.