粒子群优化在最大熵法定量织构分析中的应用

APPLYING PARTICLE SWARM OPTIMIZATION TO QUANTITATIVE TEXTURE ANALYSIS BY MAXIMUM ENTROPY METHOD

在最大熵法的基础上,采用带有惯性权重的粒子群算法(PSO),测算了多组具有宏观对称的深冲钢板(IF钢)和冷轧纯铜片样品的完整晶粒取向分布,与用阻尼Newton法计算的结果一致,均得到了满意的结果.在测算中无需任何假设,且样品的成分、织构类型及分布状况对计算结果均无影响.

Based on maximum entropy method （MEM）, the particle swarm optimization （PSO） with inertia weight factor was effectively applied for the quantitative texture analysis, and satisfying calculation results have been obtained for complete orientation distributions of many deep-drawing steel sheets and purity copper samples with macro orthogonal symmetry. In the processing data, there is not any assumption except that the entropy is maximum, furthermore, the calculated results are not affected by the sample compositions, texture compositions as well as their orientation distributions at all.