基于遗传算法的球度误差评定

首先对球度公差评定问题进行了综述.然后根据圆度公差的数学定义,引申提出球度公差最小区域条件下的评定模型,并给出遗传算法的适应度函数.随后给出算法实现中的中的关键问题.最后用实例对算法进行了检验,计算结果表明基于遗传算法的球度误差优化算法不仅符合最小区域的条件,而且易于理解和实现,能够获得全局最优解,保证了高精度、高效率.

Sphericity error evaluation using the genetic algorithm

To evaluate the form error of a sphere, a novel method based on the genetic algorithm was devised. In the paper, the problem about sphericity error is reviewed firstly. Secondly, the mathematical model of the sphericity error under the condition of minimum zone is derived from the mathematical definition of the circularity, and the fitness function of the algorithm is given as well. Thirdly, the critical such as selecting the initial value, initialing the population, and deciding genetic operators, etc. in the process of the algorithm implementation are described in detail. Finally, the method is verified by the examples in the literatures 1 and 2. The theoretical analysis and computation results indicate that the designed method not only conforms to the minimum zone condition but also assures a global solution, and is easily implemented. It is accurate and efficient in solving the problem of dimensional and tolerance evaluation.