基于多色集合理论的机内测量规划研究

Research on in-machine measurement planning based on polychromatic sets theory

针对机内测量中复杂工件测量规划的顺序问题,在遗传算法规划测量顺序前,引入了多色集合理论。通过对测试模型建立测量约束模型和围道布尔矩阵,然后用遗传算法规划出最佳的测量顺序。相较于直接使用遗传算法,所提出的方法提前划分各待测特征测量方式,进而在工件整体上实现更加高效的优化测量顺序。通过本研究所建立的方法,可以更好地规划机内检测方案,快速、准确地完成工件测量任务,进一步提高工业生产质量和效率。

To address the sequential problem of planning the measurement of complex workpieces in in-machine measurement,this paper introduces TPS before the genetic algorithm plans the measurement sequence.A measurement constraint model and an envelope Boolean matrix are established for the test model,and then a genetic algorithm is used to plan the optimal measurement sequence.Compared to the direct use of genetic algorithms,the method proposed in this paper divides the measurement methods of each feature to be measured in advance,and thus achieves a more efficient and optimised measurement sequence on the workpiece as a whole.The method established in this study allows for better planning of in-machine inspection solutions and fast and accurate workpiece measurement tasks,further improving the quality and efficiency of industrial production.