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Predicting the Tempering Curve of Tool Steel Using Neural Networks (CROSBI ID 476687)

Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija

Filetin, Tomislav ; Majetić, Dubravko ; Žmak, Irena Predicting the Tempering Curve of Tool Steel Using Neural Networks // 2. International Conference on Industrial Tools : ICIT'99 / Kuzman, Karl ; Balič, Jože (ur.). Maribor: TECOS Slovenian Tool and Die Development Centre, 1999. str. 424-427-x

Podaci o odgovornosti

Filetin, Tomislav ; Majetić, Dubravko ; Žmak, Irena

engleski

Predicting the Tempering Curve of Tool Steel Using Neural Networks

The purpose of this paper is to demonstrate how a neural network approach is used for predicting steel properties in case when some of the relevant influence factors and their relations are unknown. An attempt has been made to establish a nonlinear statis discrete-time neuron model, the so-called Static Elemntary Processor (SEP). Based on SEP neuopns, a static multi layer forward neural network is proposed to predict s tempering curve from chemical composition (%C, CR, NI, MO, W, V, Co) and austenizing temperature. In the neural network learning procedure datasets with 18 tool steel grades with different compositions are used. The mean error between hardness data from catalogue and predicted hardness data as well as standard deviation for testing dataset (8 steel grades) are very small and acceptable. These preliminary results encourage further investigation.

tool steels; neural network; prediction of tempering curve

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Podaci o prilogu

424-427-x.

1999.

objavljeno

Podaci o matičnoj publikaciji

2. International Conference on Industrial Tools : ICIT'99

Kuzman, Karl ; Balič, Jože

Maribor: TECOS Slovenian Tool and Die Development Centre

Podaci o skupu

2. International Conference on Industrial Tools

predavanje

01.01.1999-01.01.1999

Maribor, Slovenija

Povezanost rada

Strojarstvo