改进的遗传算法及其在SF_6灭弧室永磁场优化中的应用

用遗传算法对某些电磁装置进行优化设计时 ,注意到其收敛速度与交叉编码的相似程度密切相关 ,为此提出了一种基于交叉算子分析的改进遗传算法。为了增强开断空载电流的能力 ,在SF6断路器的旋弧式灭弧室中加入永久磁场。在电弧上任一点具有相同角频率的条件下 ,确定所需的磁密分布。在有限元分析的基础上磁场分布的优化结果由改进的遗传算法来获得。结果表明 ,节约了大约 2 8.7%的CPU时间 ,空载电流和短路电流的开断性能均有所改进

IMPROVED GENETIC ALGORITHM FOR THE PERMANENT MAGNETIC FIELD OPTIMIZATION IN SF_6 INTERRUPTER

From the application of genetic algorithms (GAs) to the optimal designs of some electromagnetic devices, it is found that their convergence speeds are directly affected by the similarity of crossover codes. Based on the analysis for crossover operation an improved GA is presented. For increasing the interrupting capability at no load current, permanent magnetic field is drawn into the arc-rotated interrupter of sulfur hexafluoride (SF 6) circuit breaker. Under the condition of same angular frequency at any point on arc, the desirable flux density is determined. On the basis of finite element analysis the optimal magnetic field distribution is obtained by applying improved GA. As a result 28.7 percent of CPU time is saved and the interrupting performances at no load and short circuit currents are improved.