Development of Non-contact Prediction System of Surface Roughness with Medium

DOI

10.2991/asei-15.2015.305How to use a DOI?

Keywords

roughness measurement, difference compensation, BP neural network, GLCM.

Abstract

To satisfy the requirement of surface roughness with medium measurement in the machining process, a surface roughness prediction system is developed in this paper. A process classification algorithm and a texture feature difference compensation method are proposed. Four kinds of texture feature including contrast, correlation, energy and homogeneity, are extracted from roughness specimen’s clean and containing medium surface by using GLCM (Gray level co-occurrence matrix) texture analysis method. Then the model of BP neural network is built to predict the surface roughness of seven kinds of processing technic. Finally, the experimental results show that the system which is developed based on Matlab GUI can effectively predict roughness of containing medium surface of a workpiece.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Zi Li Xu
AU  - Long Chen
AU  - Song Lu
PY  - 2015/05
DA  - 2015/05
TI  - Development of Non-contact Prediction System of Surface Roughness with Medium
BT  - Proceedings of the 2015 International conference on Applied Science and Engineering Innovation
PB  - Atlantis Press
SP  - 1536
EP  - 1542
SN  - 2352-5401
UR  - https://doi.org/10.2991/asei-15.2015.305
DO  - 10.2991/asei-15.2015.305
ID  - Xu2015/05
ER  -