Paper Title:
Milling Force Forecast of the Matching of Lengthened Shrink-Fit Holder and Cutter in High Speed Machining
  Abstract

Present work of this paper focus on developing a milling force model according to the characteristic of the matching of lengthened shrink-fit holder (LSFH) and cutter using back propagation neural network (BPNN). Time parameter is taken as a factor of the input vector besides 6 processing conditions which mainly affect the milling force, and then the forecasting of 3D transient milling forces are achieved. A lot of milling experiments were performed to get training and testing samples and a Matlab program was designed to evaluate and optimize the network. The test experiments show that the forecasting results are well agreed with the experimental results and the errors of 3D force components are less than 0.18. Besides an extended performance, the BPNN model has higher efficiency and higher accuracy than the customary analytical model.

  Info
Periodical
Advanced Materials Research (Volumes 139-141)
Edited by
Liangchi Zhang, Chunliang Zhang and Tielin Shi
Pages
827-830
DOI
10.4028/www.scientific.net/AMR.139-141.827
Citation
H. M. Zhou, J. X. Deng, W. W. Xie, "Milling Force Forecast of the Matching of Lengthened Shrink-Fit Holder and Cutter in High Speed Machining", Advanced Materials Research, Vols. 139-141, pp. 827-830, 2010
Online since
October 2010
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Price
$32.00
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