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",

}

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 - https://www.scopus.com/pages/publications/19044372114

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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