College of Mechatronics Engineering and Automation, National University of Defense Technology, Changsha 410073, China.
Sensors (Basel). 2012;12(5):6447-62. doi: 10.3390/s120506447. Epub 2012 May 15.
The long stator track for high speed maglev trains has a tooth-slot structure. The sensor obtains precise relative position information for the traction system by detecting the long stator tooth-slot structure based on nondestructive detection technology. The magnetic field modeling of the sensor is a typical three-dimensional (3-D) electromagnetic problem with complex boundary conditions, and is studied semi-analytically in this paper. A second-order vector potential (SOVP) is introduced to simplify the vector field problem to a scalar field one, the solution of which can be expressed in terms of series expansions according to Multipole Theory (MT) and the New Equivalent Source (NES) method. The coefficients of the expansions are determined by the least squares method based on the boundary conditions. Then, the solution is compared to the simulation result through Finite Element Analysis (FEA). The comparison results show that the semi-analytical solution agrees approximately with the numerical solution. Finally, based on electromagnetic modeling, a difference coil structure is designed to improve the sensitivity and accuracy of the sensor.
高速磁悬浮列车的长定子轨道具有齿槽结构。传感器通过无损检测技术检测长定子齿槽结构，为牵引系统获取精确的相对位置信息。传感器的磁场建模是一个典型的三维（3-D）电磁场问题，具有复杂的边界条件，本文采用半解析方法进行研究。引入二阶矢量位（SOVP）将矢量场问题简化为标量场问题，根据多极理论（MT）和等效新源（NES）方法，该标量场问题的解可以用级数展开表示。展开的系数根据边界条件用最小二乘法确定。然后，通过有限元分析（FEA）将解与模拟结果进行比较。比较结果表明，半解析解与数值解大致吻合。最后，基于电磁建模，设计了差分线圈结构以提高传感器的灵敏度和精度。
