TOOL WEAR PREDICTION BASED ON WAVELET TRANSFORM AND SUPPORT VECTOR MACHINES

Dongfeng Shi, Nabil N. Gindy

2011

Abstract

The machining quality and efficiency may be improved significantly by using appropriate tool wear prediction techniques. A new approach based on wavelet transform and support vector machine is proposed to improve the accuracy of tool wear prediction in this paper. Firstly, the wavelet transform is introduced to decompose sensory signals into different scales to reduce the dimensionality of original signals and extract features associated with different tool wear condition. Secondly, the least square support vector machine is further presented to construct predictive model due to its high convergence rate and powerful generalization ability. Thirdly, the possibility to employ power sensor rather than delicate dynamometer for the tool wear monitoring is explored. Finally, the effectiveness of proposed tool wear prediction approach is demonstrated by extensive experimental turning trials.

References

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Paper Citation


in Harvard Style

Shi D. and N. Gindy N. (2011). TOOL WEAR PREDICTION BASED ON WAVELET TRANSFORM AND SUPPORT VECTOR MACHINES . In Proceedings of the 8th International Conference on Informatics in Control, Automation and Robotics - Volume 2: MSIE, (ICINCO 2011) ISBN 978-989-8425-75-1, pages 479-485. DOI: 10.5220/0003647304790485


in Bibtex Style

@conference{msie11,
author={Dongfeng Shi and Nabil N. Gindy},
title={TOOL WEAR PREDICTION BASED ON WAVELET TRANSFORM AND SUPPORT VECTOR MACHINES},
booktitle={Proceedings of the 8th International Conference on Informatics in Control, Automation and Robotics - Volume 2: MSIE, (ICINCO 2011)},
year={2011},
pages={479-485},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003647304790485},
isbn={978-989-8425-75-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 8th International Conference on Informatics in Control, Automation and Robotics - Volume 2: MSIE, (ICINCO 2011)
TI - TOOL WEAR PREDICTION BASED ON WAVELET TRANSFORM AND SUPPORT VECTOR MACHINES
SN - 978-989-8425-75-1
AU - Shi D.
AU - N. Gindy N.
PY - 2011
SP - 479
EP - 485
DO - 10.5220/0003647304790485