基于微粒群算法薄钢板磁场推算中的位置优化

The Measurement Positions Optimization in Extrapolation of Steel's Magnetic Field Based on Particle Swarm Optimization Algorithm

基于积分方程法进行薄钢板两侧磁场推算时方程离散化后容易呈现病态,提出了一种依据磁场计算和剖分单元数进行测量点数的优化方法.该方法利用随机类微粒群(PSO)优化算法确定相应的测量位置分布,不但解决了测量位置优化问题,而且需要的测量点数较少,推算精度大大提高.通过钢板实验中2组不同测量位置的磁场推算实例,验证了优化位置的有效性.

Aiming at the problem that the condition number of coefficient matrix is very large after the（equation） discretization when extrapolating the steel＇s magnetic field,a new method was introduced.It can get optimal measurement positions according to magnetic field calculations and mesh of the ferromagnetic object and then the optimal measurement positions can be easily got by particle swarm optimization algorithm.The new method not only optimizes the positions,but also reduces the number of points and receives good results.In order to validate the positions,two different sets of measurement positions were used to extrapolate the sheet steel＇s magnetic field.The good results explain that the conclusion is reasonable.