Machining accuracy retainability prediction of machine tool based on least square support vector machine

DOI

10.2991/icmmita-16.2016.152How to use a DOI?

Keywords

machine tool; accuracy retainability; machining accuracy; LS-SVM.

Abstract

The accuracy retainability is becoming an important performance index of machine tool, and how to improve it is a tough problem faced to manufacturers and users. Generally, it needs to measure the errors termly and repeatedly during the specified period to analyze the timeliness machining accuracy retainability, which generates intricate and vast error data. In this paper, a solution to predict machining accuracy retainability is proposed based on least square support vector machine (LS-SVM). A vertical machining center that machines plane and hole continuously for half a year is selected as an illustrative example. The analysis results show that the proposed method is good at predicting the timeliness machining accuracy retainability of machine tool.

Copyright

© 2017, 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  - Qiang Cheng
AU  - Baobao Qi
AU  - Bingwei Sun
AU  - Guobin Yan
PY  - 2017/01
DA  - 2017/01
TI  - Machining accuracy retainability prediction of machine tool based on least square support vector machine
BT  - Proceedings of the 2016 4th International Conference on Machinery, Materials and Information Technology Applications
PB  - Atlantis Press
SP  - 817
EP  - 823
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmmita-16.2016.152
DO  - 10.2991/icmmita-16.2016.152
ID  - Cheng2017/01
ER  -