Surface Roughness Intelligent Prediction on Grinding

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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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  -