基于改进的BP神经网络的粘结NdFeB永磁体制备工艺优化设计
Optimization Planning of Preparation Process for Bonded NdFeB Permanent Magnet Based on Modified BP Neural Network
-
摘要: 采用均匀设计实验方案, 结合主成分分析方法, 建立了制备工艺与磁体性能之间的BPNN预测模型。利用该模型对粘结NdFeB永磁体的制备工艺进行了优化, 并研究了单因素以及多因素交互作用与磁体性能之间的关系。结果表明该模型预测精度较高, 对Br、Hcj及(BH) m的预测相对误差最大值分别为1.85%、1.28%和1.47%。Abstract: A BP neural network model is established between preparation process and magnetic properties by using uniform design solution and principal component analysis.This model is used to optimize the preparing process of bonded NdFeB permanent magnet.The effects of single element or the interaction among elements on magnetic properties are discussed respectively.The precision of the forecasting model is higher and the largest relative errors between the predicted and measured results are 1.85% for Br, 1.28% for Hcj, and 1.47% for (BH) m respectively.