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

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...

Full description

Saved in:
Bibliographic Details
Published inApplied Mechanics and Materials Vol. 130-134; pp. 2508 - 2512
Main Authors Li, Li Jie, Yue, Ying Gao, Ren, Xiao Hong, Xu, Wei Dong
Format Journal Article
LanguageEnglish
Published Zurich Trans Tech Publications Ltd 01.01.2012
Subjects
Texture Image
Grey Level Co-Occurrence Matrix
MATLAB GUI
Identification
BP Neural Network (BPNN)
Diagnosis
Tool Wear Condition
Online AccessGet full text

Cover

More Information
Summary: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.
Bibliography:Selected, peer reviewed papers from the 2011 3rd International Conference on Mechanical and Electronics Engineering (ICMEE 2011), September 23-25, 2011, Hefei, China
ISBN:3037852860
9783037852866
ISSN:1660-9336
1662-7482
1662-7482
DOI:10.4028/www.scientific.net/AMM.130-134.2508