Design of a Computer Vision System to Estimate Tool Wearing

Abstract:

Article Preview

Wear level of tool inserts in automated processes is tried using techniques of artificial vision. An application has been developed in Matlab that allows the acquisition of images with different resolutions and later on to process them. It is explained how the vision system used has been designed and implemented. The method for acquiring tool insert images and their treatment in the pre-processing, segmentation and post-processing is commented. First results are also presented using diverse texture descriptors. These first results must be corroborated carrying out new experiments with a bigger number of images.

Info:

Periodical:

Edited by:

M. Marcos and L. Sevilla

Pages:

61-66

Citation:

E. Alegre et al., "Design of a Computer Vision System to Estimate Tool Wearing", Materials Science Forum, Vol. 526, pp. 61-66, 2006

Online since:

October 2006

Export:

Price:

$38.00

[1] A. Weckenmann, K. Nalbantic: Precision measurement of cutting tools with two matched optical 3D-sensors. Annals of the CIRP, vol. 52, nº 1 (2003), pp.443-446.

DOI: https://doi.org/10.1016/s0007-8506(07)60621-0

[2] T. Pfeifer and L. Wiegers: Reliable tool wear monitoring by optimized image and illumination control in machine vision, Measurement, vol. 28, nº 3 (2000), pp.209-218.

DOI: https://doi.org/10.1016/s0263-2241(00)00014-2

[3] S. Kurada, C. Bradley: A review of machine vision sensor for tool condition monitoring. Computers in industry, 34 (1997), pp.55-72.

DOI: https://doi.org/10.1016/s0166-3615(96)00075-9

[4] J. Zhang, T. Tan: Brief review of invariant texture analysis methods. Pattern Recognition, Vol 35 (2002), pp.735-747.

DOI: https://doi.org/10.1016/s0031-3203(01)00074-7

[5] C. Jin, D. Wen: Review recent developments in the applications of image processing techniques for food quality evaluation, Trends in food science & technology, Vol. 15, (2004), pp.230-249.

DOI: https://doi.org/10.1016/j.tifs.2003.10.006

[6] M.H. Bharati, J.J. Liu, J.F. MacGregor, Image texture analysis: methods and comparisons. Chemometrics and Intelligent Laboratory Systems. Vol. 72 (2004), pp.57-71.

DOI: https://doi.org/10.1016/j.chemolab.2004.02.005

[7] E. Alegre, J. Barreiro, R. A. Fernández, T. Alonso: Evaluation of cutting insert wear surface using digital image. XXIV Automatic Forum, (León, Spain, 2003).

[8] E. Alegre, J. Barreiro, T. Alonso: Software for the automatic measurement of cutting insert wear using digital image. XVI Mechanical Engineering National Congress Vol. 3 (León, Spain, 2004).

Fetching data from Crossref.
This may take some time to load.