基于产品结构特征参数的实例搜索与修改方法

    Case search and adaptation based on feature parameters of products

    • 摘要: 通过建立机械产品的结构特征参数,用神经网络构建产品原始技术参数与结构特征参数之间的关系模型,映射出待求解问题的结构特征参数,之后,将结构特征参数作为实例属性,以兰氏距离为相似度量实现相似实例的搜索,从而将复杂物理结构相似判定问题转化为结构特征参数向量间距离的判定问题,得到的结构特征参数也作为修改相似实例的依据,实现产品的快速设计。论述了该模型的工作原理、结构特征参数的构建方法、神经网络映射模型的构建方法、基于兰氏距离的实例相似度计算方法,并以斗式提升机为例验证了设计模型的可行性和有效性,为实现复杂机械产品的快速智能设计提供技术支持。

       

      Abstract: By extracting the feature parameters and setting up the relation model between technical parameters and structure parameters with artificial neural network, the new feature parameters were mapped. Then this new feature parameters were regarded as the attribution of the new problem, Lance and William distance were chose as similarity measure to realize the similar case search, so the physical structure similarity searching was turned into parameter vector similarity searching and the new feature parameters were also used to modify the similar case obtained. The working principle, feature parameter extracting, ANN model and Lance and William similarity measure were discussed. The workflow and modules of the prototype for bucket elevator deign were also presented to test the feasibility of the new approach, and this research can provide technical support for rapid and intelligent design of complex products.

       

    /

    返回文章
    返回