Model of artificial neural network for optimizing technological parameter of friction welding of dissimilar material

Yu Wang; Da Lu Gao; Ming Fu Liao; Jing Feng

Model of artificial neural network for optimizing technological parameter of friction welding of dissimilar material

Yu Wang, Da Lu Gao, Ming Fu Liao, Jing Feng

School of Power and Energy

Northwestern Polytechnical University Xian

Research output: Contribution to journal › Article › peer-review

Abstract

Aiming at to difficulty to determine the parameter correctly for dissimilar material with different thermal properties, a new method for predicting key welding parameters was introduced, which was developed on the basis of the three layers of back-propagation neural network. The result showed that the predicting values are well identical with the experimental ones.

Original language	English
Pages (from-to)	33-36
Number of pages	4
Journal	Hanjie Xuebao/Transactions of the China Welding Institution
Volume	26
Issue number	4
State	Published - Apr 2005

Keywords

Forging pressure
Friction period
Friction welding
Neural network

Cite this

@article{f23fc885643f456eb9d31fb3143e459c,

title = "Model of artificial neural network for optimizing technological parameter of friction welding of dissimilar material",

abstract = "Aiming at to difficulty to determine the parameter correctly for dissimilar material with different thermal properties, a new method for predicting key welding parameters was introduced, which was developed on the basis of the three layers of back-propagation neural network. The result showed that the predicting values are well identical with the experimental ones.",

keywords = "Forging pressure, Friction period, Friction welding, Neural network",

author = "Yu Wang and Gao, {Da Lu} and Liao, {Ming Fu} and Jing Feng",

year = "2005",

month = apr,

language = "英语",

volume = "26",

pages = "33--36",

journal = "Hanjie Xuebao/Transactions of the China Welding Institution",

issn = "0253-360X",

publisher = "Harbin Research Institute of Welding",

number = "4",

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TY - JOUR

T1 - Model of artificial neural network for optimizing technological parameter of friction welding of dissimilar material

AU - Wang, Yu

AU - Gao, Da Lu

AU - Liao, Ming Fu

AU - Feng, Jing

PY - 2005/4

Y1 - 2005/4

N2 - Aiming at to difficulty to determine the parameter correctly for dissimilar material with different thermal properties, a new method for predicting key welding parameters was introduced, which was developed on the basis of the three layers of back-propagation neural network. The result showed that the predicting values are well identical with the experimental ones.

AB - Aiming at to difficulty to determine the parameter correctly for dissimilar material with different thermal properties, a new method for predicting key welding parameters was introduced, which was developed on the basis of the three layers of back-propagation neural network. The result showed that the predicting values are well identical with the experimental ones.

KW - Forging pressure

KW - Friction period

KW - Friction welding

KW - Neural network

UR - http://www.scopus.com/inward/record.url?scp=19044372114&partnerID=8YFLogxK

M3 - 文章

AN - SCOPUS:19044372114

SN - 0253-360X

VL - 26

SP - 33

EP - 36

JO - Hanjie Xuebao/Transactions of the China Welding Institution

JF - Hanjie Xuebao/Transactions of the China Welding Institution

IS - 4

ER -

Model of artificial neural network for optimizing technological parameter of friction welding of dissimilar material

Abstract

Keywords

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