DocumentCode :
2741097
Title :
Signal Decomposition Based Approach on Status Recognition of Four Flutes End Milling Cutter
Author :
Liu, Can ; Yao, Xifan ; Lu, Bin ; Liu, Yan
Author_Institution :
Coll. of Eng., Guangdong Ocean Univ., Zhanjiang
Volume :
2
fYear :
0
fDate :
0-0 0
Firstpage :
7963
Lastpage :
7968
Abstract :
Significant index and adaptive algorithm are necessary for recognizing status of milling cutter. The cutting-force-signal wave was decomposed into valley and amplitude, and formulas were deduced to represent their changes when a flute is broken, in feed direction, the ratio of amplitude value to valley value increases, while that in normal direction decreases. Force power spectrum at tooth rotational frequency and that at spindle rotational frequency represents amplitude value and valley value individually, so their ratios in feed and normal directions were taken as signal features, meanwhile, linear machine algorithm was improved and used, with which the experimental milling-tool data are well clustered, this result shows that the index and algorithm are effective
Keywords :
cutting tools; machine tool spindles; milling; pattern clustering; signal processing; adaptive algorithm; breakage index; cutting-force-signal wave; flutes end milling cutter; force power spectrum; linear machine algorithm; signal decomposition; spindle rotational frequency; status recognition; tooth rotational frequency; Adaptive algorithm; Clustering algorithms; Educational institutions; Feeds; Frequency; Marine technology; Mechanical engineering; Milling; Oceans; Signal resolution; breakage index; end milling; linear machine; status recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on
Conference_Location :
Dalian
Print_ISBN :
1-4244-0332-4
Type :
conf
DOI :
10.1109/WCICA.2006.1713522
Filename :
1713522
Link To Document :
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