基于遗传算法的等距型面误差测量

Measuring Isometric Polygon Error Based on Genetic Algorithm

等距型面轮廓曲线为非圆曲线的一种,对其参数的测量和误差的计算比较困难,目前尚没有统一的评价标准。根据圆的测量方法,选用最小包容区域法来评定距型面的轮廓参数及其误差并建立了相应的求解数学模型。由于其数学模型的求解过程是一个多目标优化的复杂过程,所以采用了遗传算法对该数学模型进行了求解。结果表明该方法提高了等距型面轮廓曲线的参数和误差的测量精度,为等距型面的精确测量提供了新的计算方法。

The outlining curve of an isometric polygon is one of the un-rounded curves, it is difficult to measure its parameters and calculate the errors. At present, there isn＇t any unified standard for evaluation. In accordance with the measuring method for rounded shape, by using minimum enveloping principle, the outlining parameters of polygon and errors are evaluated. In addition, relevant mathematical model for solutions is created. It is a complicated multi-objective optimization process, so a genetic algorithm is used. The result indicates that the measurement accuracy of the parameters and errors is improved, and it supplies a new processing method for measuring isometric polygonal curves.