Use of Artificial Neural Network in Predicting Mechanical Properties of High-Speed Steel (HSS)

Author

Liujie, Xu ; Jiandong, Xing ; Shizhong, Wei ; Songmin, Zhang ; Yongzhen, Zhang ; Rui, Long

Author_Institution

State Key lab. for Mech. Behavior of Mater., Xi´´an Jiaotong Univ.

fYear

2006

fDate

25-28 June 2006

Firstpage

1872

Lastpage

1877

Abstract

This paper is dedicated to the application of artificial neural networks in building prediction models of mechanical properties of new high-speed steel, including predictions of hardness (H) and impact toughness (Ak) according to quenching and tempering temperatures (T1, T2). multilayer backpropagation (BP) networks are created and trained using comprehensive datasets tested by the authors. And very good performances of the neural networks are achieved. The prediction values sufficiently mine the basic domain knowledge of heat treatment process of HSS. A new application field of neural network was developed by the authors

Keywords

backpropagation; hardness; impact (mechanical); mechanical engineering computing; neural nets; steel; artificial neural network; hardness prediction; high-speed steel; impact toughness; mechanical properties prediction; multilayer backpropagation networks; Artificial neural networks; Backpropagation; Heat treatment; Mechanical factors; Multi-layer neural network; Neural networks; Predictive models; Steel; Temperature; Testing; BP neural network; heat treatment temperature; high-speed steel; mechanical property;

fLanguage

English

Publisher

ieee

Conference_Titel

Mechatronics and Automation, Proceedings of the 2006 IEEE International Conference on

Conference_Location

Luoyang, Henan

Print_ISBN

1-4244-0465-7

Electronic_ISBN

1-4244-0466-5

Type

conf

DOI

10.1109/ICMA.2006.257520

Filename

4026379