Experimental Research on the Crack Identification of Drawing Parts Based on AE Technique

Zhi Gao Luo; Bao Gang Zhang; Xin He

doi:10.4028/www.scientific.net/AMM.141.275

Paper Titles

Development of an Ontology-Based and STEP-Compliant Intelligent CNC System
p.251

Digitally Reverse Modeling for the Repair of Blades in Aero-Engines
p.258

Error Analysis and Calibration of Gyro-Stabilized Platform for Electro-Optical Pointing System
p.264

Evaluation and Design of SNS User Interface in Handheld Device Based on Fuzzy Clustering
p.270

Experimental Research on the Crack Identification of Drawing Parts Based on AE Technique
p.275

Extraction of Frequency-Variable Characteristics and Analysis of Modulation Mechanism under Periodic Excitation
p.279

Failure Mode, Effect and Criticality Analysis of CNC Grinder
p.284

Finite Element Analysis of the Helical Surface Cutting Tool
p.289

Finite Element Simulation of Extremely High Speed Machining of Ti6Al4V Alloy
p.293

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 141Experimental Research on the Crack Identification...

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.

You might also be interested in these eBooks

Functional Manufacturing and Mechanical Dynamics II

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volume 141)

Pages:

275-278

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.141.275

Citation:

Cite this paper

Online since:

November 2011

Authors:

Zhi Gao Luo, Bao Gang Zhang, Xin He

Keywords:

Acoustic Emission (AE), Crack Identification, Drawing Parts, Experimental Research

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] Kentaro Ohno , Masayasu Ohtsu: Construction and Materials Vol. 12 (2010), pp.2339-2346.

Google Scholar

[2] T. Jayakumar, C. K. Mukhopadhyay, S. Venugopal, S. L. Mannan and Baldev Raj: Journal of Materials Processing Technology India Vol. 159 (2005), pp.48-61.

Google Scholar

[3] Li Nan, Wang Enyuan, Hao Enlai, MaYankun, Xu Fulei, Qian Weihua: Journal of China Coal Society (2010) No. 7, pp.1099-1103.

Google Scholar

[4] Tirian, GeluOvidiu; Camelia, PincaBretotean; RuPradipK. Saha: Wear Vol. 218(1998) , pp.179-190.

Google Scholar

[5] Hu Hongjun, Zhang Dingfei, Pan Fusheng, Yang Mingbo: Acta Metallurgica Sinica Vol. 22(2009) No. 5, pp.53-64.

Google Scholar