DocumentCode :
477479
Title :
NdFeB Magnet Composite Design Based on BP Network
Author :
Huiyu Wang ; Yuanhua Ren ; Jianfeng Pan
Author_Institution :
Coll. of Comput. Sci. & Technol., Zhejiang Univ., Hangzhou
Volume :
1
fYear :
2008
fDate :
20-22 Oct. 2008
Firstpage :
204
Lastpage :
208
Abstract :
Traditionally, the composite design of NdFeB magnet was consuming with repeated experiments. In order to speed up the design process of NdFeB magnet, BP network is trained to model the relationship between NdFeB magnet composition and the magnetic properties. The training data that come from production data are classified into two groups for the purpose of simplifying the network structure and improving the efficiency of the training. The experiment results of regression analysis indicate that the predicted data are consistent with the measured data quite well. The tendencies of the magnetic properties are also forecasted in the experiment results, which will guide the NdFeB magnet composite designing.
Keywords :
backpropagation; boron alloys; data handling; iron alloys; materials science computing; neodymium alloys; neural nets; pattern classification; permanent magnets; regression analysis; BP network; NdFeB; NdFeB magnet composite design; magnetic properties; network structure; regression analysis; training data; Artificial neural networks; Biological system modeling; Intelligent networks; Magnetic properties; Neural networks; Neurons; Predictive models; Process design; Production; Training data; BP Network; NdFeB magnet design; properties forecasting; training data classify;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Computation Technology and Automation (ICICTA), 2008 International Conference on
Conference_Location :
Hunan
Print_ISBN :
978-0-7695-3357-5
Type :
conf
DOI :
10.1109/ICICTA.2008.160
Filename :
4659473
Link To Document :
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