Proceedings of the 3rd International Conference on Material, Mechanical and Manufacturing Engineering

Surface Roughness Intelligent Prediction on Grinding

Authors
Dingtong Zhang, Ning Ding
Corresponding Author
Dingtong Zhang
Available Online August 2015.
DOI
10.2991/ic3me-15.2015.415How to use a DOI?
Keywords
grinding, surface roughness, prediction, fuzzy neural network, AE
Abstract

Grinding is generally the final process, and it is closely related with the surface quality of the component. Now, it’s difficult to measure the surface roughness until the grinding process is finished. The purpose of this research was to study the roughness prediction and avoid the defect happening in the grinding process. A surface roughness prediction model was built using the acoustic emission (AE) signal and Fuzzy- neural networks. Tests were performed, and the result verifies the feasibility of the proposed model.

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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Volume Title
Proceedings of the 3rd International Conference on Material, Mechanical and Manufacturing Engineering
Series
Advances in Engineering Research
Publication Date
August 2015
ISBN
978-94-6252-100-1
ISSN
2352-5401
DOI
10.2991/ic3me-15.2015.415How to use a DOI?
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/).

Cite this article

TY  - CONF
AU  - Dingtong Zhang
AU  - Ning Ding
PY  - 2015/08
DA  - 2015/08
TI  - Surface Roughness Intelligent Prediction on Grinding
BT  - Proceedings of the 3rd International Conference on Material, Mechanical and Manufacturing Engineering
PB  - Atlantis Press
SP  - 2166
EP  - 2169
SN  - 2352-5401
UR  - https://doi.org/10.2991/ic3me-15.2015.415
DO  - 10.2991/ic3me-15.2015.415
ID  - Zhang2015/08
ER  -