Investigation of Optimal Megnetic Properties in NdFeB Magnets by Artificial Neural Network
来源期刊：JOURNAL OF RARE EARTHS2004年增刊第1期
论文作者：Hu Wang Tu Mingjing Lian Lixian Hou Tinghong Liu Ying Gao Shengji
Key words：metal materials; artificial neural network; uniform design; NdFeB; magnetic properties; rare earths;
Abstract: In order to study the effect of alloy component on magnetic properties of NdFeB magnets, the experiment schemes are carried out by the uniform design theory, and the relationship between the component and the magnetic properties is established by artificial neural network(ANN) predicting model.The element contents of alloys are optimized by the ANN model.Meanwhile, the influences of mono-factor or multi-factor interaction on alloy magnetic properties are respectively discussed according to the curves ploted by ANN model.Simulation result shows that the predicted and measured results are in good agreement.The relative error is every low, the error is not more than 1.68% for remanence Br, 1.56% for maximal energy product (BH)m, and 7.73% for coercivity Hcj.Hcj can be obviously improved and Br can be reduced by increasing Nd or Zr content.Co and B have advantageous effects on increasing Br and disadvantageous effects on increasing Hcj.Influence of alloying elements on Hcj and Br are inverse, and the interaction among the alloying elements play an important role in the magnetic properties of NdFeB magnets.The ANN prediction model presents a new approach to investigate the nonlinear relationship between the component and the magnetic properties of NdFeB alloys.
Hu Wang1，Tu Mingjing2，Lian Lixian2，Hou Tinghong2，Liu Ying2，Gao Shengji2
(1.School of Computer Science & Engineering, Sichuan University, Chengdu 610065, China;
2.College of Materials Science & Engineering, Sichuan University, Chengdu 610065, China)
Abstract:In order to study the effect of alloy component on magnetic properties of NdFeB magnets, the experiment schemes are carried out by the uniform design theory, and the relationship between the component and the magnetic properties is established by artificial neural network(ANN) predicting model.The element contents of alloys are optimized by the ANN model.Meanwhile, the influences of mono-factor or multi-factor interaction on alloy magnetic properties are respectively discussed according to the curves ploted by ANN model.Simulation result shows that the predicted and measured results are in good agreement.The relative error is every low, the error is not more than 1.68% for remanence Br, 1.56% for maximal energy product (BH)m, and 7.73% for coercivity Hcj.Hcj can be obviously improved and Br can be reduced by increasing Nd or Zr content.Co and B have advantageous effects on increasing Br and disadvantageous effects on increasing Hcj.Influence of alloying elements on Hcj and Br are inverse, and the interaction among the alloying elements play an important role in the magnetic properties of NdFeB magnets.The ANN prediction model presents a new approach to investigate the nonlinear relationship between the component and the magnetic properties of NdFeB alloys.
Key words:metal materials; artificial neural network; uniform design; NdFeB; magnetic properties; rare earths;
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