SVD analysis of a machined surface image for the tool wear estimation / Anna Zawada-Tomkiewicz, Borys Storch.
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W: Proceedings of the 5th International Conference of DAAAM Baltic Industrial Engineering - Adding Innovation Capacity / ed. by R. Kyttner. - Tallinn : University of Technology, 2006. - s. 171-176Streszczenie: Image of e machined surface is the perspective projection of a magnified surface on a convereter plane. Cutting condition deterioration and tool wear influence the image of the machined surface. Change in image is distinctly noticeable from the energetic point of view. Singular value decomposition (SVD) method is a factorisation technique which effectively reduces machined surface image into a smaller portion of data. Analysis of the eigenvalues of a machined surface image makes possible their application in the estimation of tool wear.
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Image of e machined surface is the perspective projection of a magnified surface on a convereter plane. Cutting condition deterioration and tool wear influence the image of the machined surface. Change in image is distinctly noticeable from the energetic point of view. Singular value decomposition (SVD) method is a factorisation technique which effectively reduces machined surface image into a smaller portion of data. Analysis of the eigenvalues of a machined surface image makes possible their application in the estimation of tool wear.