Possible Way to Diminish the Effect of Chatter in CNC Turning Based on EMD and ANN Approaches

被引:0
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作者
Y. Shrivastava
B. Singh
机构
[1] Jaypee University of Engineering and Technology,Mechanical Engineering Department
关键词
Tool chatter; Data acquisition; Empirical mode decomposition; Intrinsic mode function; Artificial neural network;
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摘要
Tool chatter is responsible for the poor surface finish and lower productivity. Despite the immense work done within this domain to increase the productivity and surface finish simultaneously, still many aspects related to regenerative chatter remain un-explored. In this research work, an optimal cutting zone has been predicted using well-established techniques, viz. empirical mode decomposition and artificial neural network. Machining in the obtained zone will increase the productivity, by decreasing tool chatter and increasing material removal rate simultaneously. To validate the proposed methodology as a suitable and possible way to reduce the effect of chatter, more experiments have been performed within the obtained optimal zone. The results indicate the effectiveness of the proposed methodology.
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页码:4571 / 4591
页数:20
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