Monitoring of tool wear using Feature Vector Selection and Linear Regression

Lecture Notes in Computer Science

Volumn 3611, Issue PART II, 2005, Pages 1-6

  Chen, Zhong ^a   Zhang, Xianming ^a  

^a SOUTH CHINA UNIVERSITY OF TECHNOLOGY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; REAL TIME SYSTEMS; REGRESSION ANALYSIS; TOOLS; VECTORS;

FEATURE VECTOR SELECTION (FVS); TOOL WEAR;

WEAR OF MATERIALS;

EID: 26844471748     PISSN: 03029743     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1007/11539117_1     Document Type: Conference Paper

References (6)

1. Du, R.X., Elbestawi, M.A., Li, S.: Tool Condition Monitoring in Turning Using Fuzzy Set Theory. International Journal of Machine Tools and Manufacture, Vol.32, No.6, (1992) 781-796
2. Brezak, D., Udiljak, T., Mihoci, K., Majetic, D., Novakovic, B., Kasac, J.: Tool wear monitoring using radial basis function neural network. Proceedings of 2004 IEEE International Joint Conference on Neural Networks, Vol.3, (2004) 1859-1862
3. Tansel, I.N., Mekdeci, C., McLaughlin, C.: Detection of Tool Failure in End Milling with Wavelet Transformations and Neural Networks (WT-NN), International Journal of Machine Tools and Manufacture, vol.35, no.8 (1995) 1137-1147
4. Li, S., Yao, Y., Yuan, Z.: On-line Tool Condition Monitoring with Improved Fuzzy Neural Network, High Technology Letters, vol.3, no. 1 (1997) 30-33
5. Sun, J., Hong, G. S., Rahman, M., Wong, Y. S.: The Application of Nonstandard Support Vector Machine in Tool Condition Monitoring System. Second IEEE International Workshop on Electronic Design, Test and Applications (2004) 295-300
6. Baudat G., Anouar F.: Feature vector selection and projection using kernel. Neurocomputing, Vol.55 (2003) 21-38