Details
| Original language | English |
|---|---|
| Pages | 39-47 |
| Number of pages | 9 |
| Volume | 67 |
| Issue number | 1 |
| Journal | HTM - Haerterei-Technische Mitteilungen |
| Publication status | Published - 2012 |
Abstract
The production of pinion shafts having a predefined hardness distribution faces the challenge of analytically describing the relationship between pinion shafts hardness and spray cooling parameters. The present work attempts to establish this type of mutual relationship based on radial basis function (RBF) neural networks regarding precision forged and spray-cooled pinion shafts. A method for increasing the ability of generalising RBF-Networks via fuzzy inputs is discussed. The results indicate that the relationship between the pinion shaft's hardness and spray cooling has been obtained by using the proposed network. The optimum process parameters can be selected to achieve the desired hardness profile on the basis of the predicted results.?
Keywords
- Fuzzification, Neural networks, Pinion shaft, Radial basis function, Spray cooling
ASJC Scopus subject areas
- Materials Science(all)
- Metals and Alloys
- Engineering(all)
- Industrial and Manufacturing Engineering
- Materials Science(all)
- Materials Chemistry
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In: HTM - Haerterei-Technische Mitteilungen, Vol. 67, No. 1, 2012, p. 39-47.
Research output: Contribution to specialist publication › Contribution in non-scientific journal › Transfer
}
TY - GEN
T1 - Modeling the relationship between hardness and spray cooling parameters for pinion shafts using a neuro-fuzzy model strategy
AU - Yu, Z.
AU - Kuznietsov, K.
AU - Mozgova, I.
AU - Böhm, V.
AU - Gretzki, T.
AU - Nürnberger, F.
AU - Schaper, M.
AU - Reimche, W.
PY - 2012
Y1 - 2012
N2 - The production of pinion shafts having a predefined hardness distribution faces the challenge of analytically describing the relationship between pinion shafts hardness and spray cooling parameters. The present work attempts to establish this type of mutual relationship based on radial basis function (RBF) neural networks regarding precision forged and spray-cooled pinion shafts. A method for increasing the ability of generalising RBF-Networks via fuzzy inputs is discussed. The results indicate that the relationship between the pinion shaft's hardness and spray cooling has been obtained by using the proposed network. The optimum process parameters can be selected to achieve the desired hardness profile on the basis of the predicted results.?
AB - The production of pinion shafts having a predefined hardness distribution faces the challenge of analytically describing the relationship between pinion shafts hardness and spray cooling parameters. The present work attempts to establish this type of mutual relationship based on radial basis function (RBF) neural networks regarding precision forged and spray-cooled pinion shafts. A method for increasing the ability of generalising RBF-Networks via fuzzy inputs is discussed. The results indicate that the relationship between the pinion shaft's hardness and spray cooling has been obtained by using the proposed network. The optimum process parameters can be selected to achieve the desired hardness profile on the basis of the predicted results.?
KW - Fuzzification
KW - Neural networks
KW - Pinion shaft
KW - Radial basis function
KW - Spray cooling
UR - http://www.scopus.com/inward/record.url?scp=84862565811&partnerID=8YFLogxK
U2 - 10.3139/105.110125
DO - 10.3139/105.110125
M3 - Contribution in non-scientific journal
AN - SCOPUS:84862565811
VL - 67
SP - 39
EP - 47
JO - HTM - Haerterei-Technische Mitteilungen
JF - HTM - Haerterei-Technische Mitteilungen
SN - 0341-101X
ER -