基于知识图谱的工艺决策方法研究

Research on craft decision making method based on knowledge graph

  • 摘要: 在CAPP系统集成、工具化和智能化的发展中,工艺方案的决策推理和智能技术是关键。传统工艺决策方法存在不能在多工艺方案中在做出智能化选择的问题,针对这一问题,提出一种基于知识图谱表示学习的工艺决策推理方法。在该方法中使用翻译距离模型对工艺知识进行向量化表示,利用向量运算得到理想结果与决策结果之间的距离,再经模型训练后使距离不断缩小致使损失函数趋于稳定,最终决策出最优结果,将结果经过模糊函数计算分析加强决策方案的合理性,解决了多工艺方案中智能决策的问题。文章以P0级6203轴承为例对所提方法进行了试验验证,结果表明,所提方法能够有效实现对零件工艺方案的决策,提高CAPP系统智能决策的能力。

     

    Abstract: In the development of CAPP system integration, instrumentalization and intelligence, decision reasoning and intelligent technology of craft scheme are the key points. Traditional craft decision making method has the problem that it can not make intelligent choice in multi-craft scheme. To solve this problem, a craft decision reasoning method based on knowledge graph representation learning was proposed. In this method, the translation distance model is used to represent the craft knowledge vectorially, and the distance between the ideal result and the decision result is obtained by vector operation. After model training, the distance is constantly reduced, which leads to the stability of the loss function. Finally, the optimal result is obtained, and the rationality of the decision scheme is strengthened by fuzzy function calculation and analysis. The problem of intelligent decision in multi-craft scheme is solved. In this paper, P0 class 6203 bearing is used as an example to verify the proposed method. The results show that the proposed method can effectively realize the decision-making of the parts craft scheme and improve the ability of intelligent decision-making of the CAPP system.

     

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