Paper Title:
Research of Tool Wear Condition Recognition Diagnosis System Based on the Machined Workpiece Surface Texture Image
  Abstract

Aiming at the machined workpiece surface texture images,some technology about image pre-processing and the texture feature extraction based on gray level co-occurrence matrix are researched. Then it is time for the analysis of the texture characteristic parameters based on BP neural network and the identification and diagnosis of tool wear state, Finally the recognition diagnosis system interface is designed by Matlab-GUI.System simulation shows that the interface fusion of image processing and neural network is a good way to ensure the realization of tool wear condition recognition,what’more, the identification diagnosis rate is profect.

  Info
Periodical
Edited by
Han Zhao
Pages
2508-2512
DOI
10.4028/www.scientific.net/AMM.130-134.2508
Citation
W. D. Xu, X. H. Ren, L. J. Li, Y. G. Yue, "Research of Tool Wear Condition Recognition Diagnosis System Based on the Machined Workpiece Surface Texture Image", Applied Mechanics and Materials, Vols. 130-134, pp. 2508-2512, 2012
Online since
October 2011
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