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Modeling tool wear in end-milling using enhanced GMDH learning networks

✍ Scribed by Godfrey C. Onwubolu; Petr Buryan; Frank Lemke


Publisher
Springer
Year
2007
Tongue
English
Weight
276 KB
Volume
39
Category
Article
ISSN
0268-3768

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In recent past, several neural network models which employ cutting forces and AErms or their derivatives for estimation as well as classification of flank wear have been developed. However, a significant variation in mean cutting forces and AErms at the start of cutting operation for similar new too