Paper Title:
Experimental Research on the Crack Identification of Drawing Parts Based on AE Technique
  Abstract

The paper performs an experimental research on the crack identification of drawing parts using AE technique. Under the platform of the AE system, the AE signals of drawing parts crack are acquired. BP neural network is designed with three layers. They are ten neurons of input layer, three neurons of output layer and thirteen neurons of hidden layer. The characteristic parameters of the crack acoustic emission are considered as the input of BP neural network to exercise the network. The test data are inputted to the neural network after it is exercised. The test result is in accord with the experiment result. The method is proper to identify the crack of drawing parts. The emergence of many inferior parts and the waste of resource can be avoided. It also can debase the cost of manufacture and improve the productive efficiency.

  Info
Periodical
Chapter
Chapter 3: Functional Manufacturing and Information Technology
Edited by
Hun Guo, Taiyong Wang, Zeyu Weng, Weidong Jin, Shaoze Yan, Xuda Qin, Guofeng Wang, Qingjian Liu and Zijing Wang
Pages
275-278
DOI
10.4028/www.scientific.net/AMM.141.275
Citation
Z. G. Luo, B. G. Zhang, X. He, "Experimental Research on the Crack Identification of Drawing Parts Based on AE Technique", Applied Mechanics and Materials, Vol. 141, pp. 275-278, 2012
Online since
November 2011
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Price
$32.00
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