A point cloud deep neural network metamodel method for aerodynamic prediction

Aiming to reduce the high expense of 3-Dimensional (3D) aerodynamics numerical simulations and overcome the limitations of the traditional parametric learning methods, a point cloud deep learning non-parametric metamodel method is proposed in this paper. The 3D geometric data, corresponding to the object boundaries, are chosen as point clouds and a deep learning neural network metamodel fed by the point clouds is further established based on the PointNet architecture. This network can learn an end-to-end mapping between spatial positions of the object surface and CFD numerical quantities. With the proposed aerodynamic metamodel approach, the point clouds are constructed by collecting the coordinates of grid vertices on the object surface in a CFD domain, which can maintain the boundary smoothness and allow the network to detect small changes between geometries. Moreover, the point clouds are easily accessible from 3D sensors. The point cloud deep learning neural network, which employs re-sampling technique, the spatial transformer network and the fully connected layer, is developed to predict the aerodynamic characteristics of 3D geometry. The effectiveness of the proposed metamodel method is further verified by aerodynamic prediction and robust shape optimization of the ONERA M6 wing. The results show that the proposed method can achieve more satisfactory agreement with the experimental measurements compared to the parametric-learning-based deep neural network.     

航空磁探中潜艇磁场建模方法分析

为提高航空磁探中潜艇磁场模型精度,分析现有潜艇磁场建模方法,对边界积分法、有限元法、积分方程法、磁体模拟法等主要潜艇磁场建模方法的基本原理和推导过程进行分析。通过数值分析比较各方法的建模精度,最后归纳潜艇低空磁场建模方法的基本要点。     

表贴式永磁直线同步电机控制系统参数自动整定方法

针对表贴式永磁直线同步电机矢量控制系统参数设置需反复测量和调试的问题,提出一种自动整定的方法。测量电流控制器输出波形并计算相应的沃尔什一阶系数,反复迭代反电动势常数和定子电感,直至沃尔什一阶系数收敛到零,自动辨识表贴式永磁直线同步电机的电气参数；随后让电机自由运行辨识出机械参数；最后计算出速度和电流控制器的PI参数。样机测试结果验证了提出方法的有效性。     

基于三维原子磁强计的核磁共振陀螺仪实验优化

核磁共振陀螺仪内嵌三维原子磁强计是实现核磁共振陀螺仪小型化的一种有效途径,故介绍了一种基于三维原子磁强计的核磁共振陀螺仪.对影响三维原子磁强计性能的重要参数进行了优化,得到了较优的x轴、yy轴和z轴磁强计信号标度因子,进而实现了更灵敏的三维原子磁强计.在三维磁场闭环锁定6000 s后,测得核磁共振陀螺仪的角度随机游走和零偏稳定性分别为0.038(°)/h1/2和0.94(°)/h.