DocumentCode
436355
Title
CNC tool wear detection using neuro-fuzzy classification system
Author
Moavenian, M. ; Moghaddam, E.T.
Author_Institution
Ferdowsi University of Mashad, Iran
Volume
17
fYear
2004
fDate
June 28 2004-July 1 2004
Firstpage
471
Lastpage
476
Abstract
Wide spread implementation of milling process in automated manufacturing has made an inevitable need for on-line knowledge of tool condition. The major problems facing are the complexity of the methods available for monitoring the tool wear and means of reliable sensing and data processing. The approach proposed in this paper has considered these while a fuzzy-neuro classification (ANFIS) for detection of tool wear employs simulated online data captured from X-axis drive of a CNC milling machine. Simulated results demonstrate successful detection of changes in tool wear state.
Keywords
Adaptive control; Clustering algorithms; Computer numerical control; Data processing; Fuzzy sets; Fuzzy systems; Mathematical model; Mechanical engineering; Metalworking machines; Milling; Fuzzy Classification; Milling operation; Neuro-Fuzzy system; Tool Wear;
fLanguage
English
Publisher
ieee
Conference_Titel
Automation Congress, 2004. Proceedings. World
Conference_Location
Seville
Print_ISBN
1-889335-21-5
Type
conf
Filename
1439411
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