摘要
针对有限元法计算量大的不足,用神经网络模拟有限元的分析过程,建立了求解漏磁场计算的有限元神经网络模型,并采用共轭梯度学习算法,对矩形缺陷的漏磁场进行了计算。通过计算得到了磁场强度、磁感应强度矢量图以及漏磁通密度x、y分量图。结果表明,有限元神经网络能够实现漏磁场的并行求解,具有速度快、稳定性好等优点,是一种漏磁场的快速计算方法。
To reduce computational cost of FEM,a neural network was adopted to simulate the process of finite element analysis,a finite element neural network（FENN） model to calculate the leakage field was established,and a conjugate gradient（CG） method was introduced as a learning algorithm.The magnetic leakage field of a rectangle defect was calculated by using FENN.The magnetic field intensity,magnetic flux density and the x and y components of leakage magnetic flux were obtained.The results indicate that the method has the advantages of rapidness and stability and can be applied to leakage field＇s parallel resolving.
出处
《兵工学报》
EI
CAS
CSCD
北大核心
2011年第11期1395-1398,共4页
Acta Armamentarii
基金
河北省自然科学基金资助项目(E2008001258)
关键词
电磁学
漏磁
电磁计算
共轭梯度法
有限元神经网络
electromagnetics
magnetic flux leakage
electromagnetic calculation
conjugate gradient algorithm
finite element neural network
