Development of Non-contact Prediction System of Surface Roughness with Medium
- 10.2991/asei-15.2015.305How to use a DOI?
- roughness measurement, difference compensation, BP neural network, GLCM.
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.
- © 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/).
Cite this article
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 -