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ID 17841
Eprint ID
17841
FullText URL
Author
Inoue, Shinichiro
Konishi, Masami
Abstract
In this research, an image processing method and a system for inspection support of a rod figured cutting tool are developed. As is well known, the visual inspection of a cutting tool by image processing is not easy, because cutting blade have a helical blade structure. To cope with the problem, an experimental facility with rotation and longitudinal tool shift functions to enable acquisition of blade surface pictures along a cutting rod is developed. The type of the defect treated in this paper is the spot of coating on blade surface. To judge the quality of the processed image of blade surface, neural network with autonomous learning is used. The processed image of cutting tool is divided into 64 × 64 blocks used for the input to the neural networks. Before input, each block data is preprocessed applying a edge detection filter and a transformation by the discrete fourier transform (DFT). Using these technologies, the experimental inspection system is built and tested to check the capabilities of the inspection algorithms. The diagnostic performance of the surface defect of a cutting tool was confirmed. There remained a problem to mis judge the normal tools as the defect.
Published Date
2009-01
Publication Title
Memoirs of the Faculty of Engineering, Okayama University
Publication Title Alternative
岡山大学工学部紀要
Volume
volume43
Publisher
Faculty of Engineering, Okayama University
Publisher Alternative
岡山大学工学部
Start Page
55
End Page
60
ISSN
1349-6115
NCID
AA12014085
Content Type
Departmental Bulletin Paper
language
英語
File Version
publisher
Refereed
False
Eprints Journal Name
mfe