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Detection of the Tool Wear Condition Based on the Computer Image Processing

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Abstract:

The tool wear detection system based on the image processing and computer vision has better study value and foreground. The paper brings forward the detection method of the tool wear condition, which solves the two main problems. Firstly, gets the high quality images by fuzzy restoration arithmetic. Because the cutting tool is always at the movement state during the cutting, the real-time collected sequence images by CCD sensor are blurred with noise. Then, obtains the character parameter uniformity Q2 by calculating gray co-occurrence matrix, which can distinguish the cutting tool is weared or not weared. The experimental results indicate that detection of the tool wear condition by computer image processing reach our aim.

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Periodical:

Key Engineering Materials (Volumes 375-376)

Pages:

553-557

DOI:

https://doi.org/10.4028/www.scientific.net/KEM.375-376.553

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Online since:

March 2008

Authors:

Ya Liang Wang, Shi Ming Ji, Li Zhang, Shou Song Jin, Yong Chen

Keywords:

Condition Detection, Fuzzy Restoration Arithmetic, Gray Co-Occurrence Matrix, Image Processing, Tool Wear

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© 2008 Trans Tech Publications Ltd. All Rights Reserved

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References

[1] X. Li, S. Dong and P.K. Venuvinod: International Journal of Advanced Manufacturing Technology, Vol. 16 (2000) No. 5, p.303.

Google Scholar

[2] D. Li and J. Mathew: International Journal of Machine Tools & Manufacture, Vol. 30 (1990) No. 4, p.579.

Google Scholar

[3] M.Y. Yang and O.D. Kwon: Control Engineering Practice, Vol. 6 (1998) No. 11, p.1389.

Google Scholar

[4] M.A. Mannan, A. Kassim and J. Ma: Pattern Recognition Letters, Vol. 21 (2000) No. 11, p.969.

Google Scholar

[5] S. Kurada and C. Bradley: Tribology International, Vol. 30 (1997) No. 4, p.295.

Google Scholar

[6] A.G. Rong: Computer Image Processing (Tsinghua University Press, China 2000).

Google Scholar

[7] Y.N. Wang, S.T. Li and J.X. Mao: Computer Image Processing and Recognition Technology (Higher Education Publications, China 2001).

Google Scholar

[8] K.R. Castleman: Digital Image Processing (Tsinghua University Press and Prentice Hall, China 1998).

Google Scholar

[9] F. Xu and X.H. Shi: MATLAB Image Processing (XiDian University Press, China 2002).

Google Scholar

[10] X.G. Liu, J.M. Wei and Z.C. Zhu: Fuzzy Control Technology (China Textile Press, China 2001).

Google Scholar

[11] Y.L. Wang, S.M. Ji and et al: Key Engineering Materials, Vol. 315-316 (2006).

Google Scholar