基于牛牙几何特征的仿生研磨副结构协同设计

doi:10.3901/JME.2024.19.212

摘要/Abstract

摘要： 研磨副表面形状是制约粉体加工质量的关键因素。面向粉体加工领域高细度、低温升的粉碎需求，围绕典型旋转式研磨副性能提升，受反刍动物牙齿功能机制启发，建立一种基于牛牙几何特征的仿生多级研磨副结构协同设计新方法。采用逆向工程重构牛牙的三维模型，通过仿生耦元提取与表征，对仿生多级研磨副结构进行设计；引入离散单元法模拟半夏破碎过程，构建仿生研磨副结构参数与破碎率、破碎热和断裂时长的Kriging代理模型，提出一种混合加点动态更新代理模型与NSGA-II算法结合的仿生多级研磨副结构参数多目标优化方法，实现仿生多级研磨副最佳结构参数集成，并通过试验对该设计方法的有效性进行验证分析。

关键词: 研磨副, 牛牙, 仿生设计, 结构优化

Abstract: The surface shape of grinding pair is a key factor restricting the quality of powder processing.Aiming at the grinding requirements of high fineness and low temperature rising in the field of powder processing, around the performance improvement of typical rotary grinding pairs, a new method of bionic multi-stage grinding pair structure collaborative design based on the geometric characteristics of bovine teeth is established inspired by the functional mechanism of ruminant teeth.The three-dimensional model of bovine teeth is reconstructed by reverse engineering, and the bionic multi-stage grinding pair structure is designed by bionic coupling element extraction and characterization.The discrete element method is introduced to simulate the crushing process of Pinellia ternata, and the Kriging model between the structural parameters of the bionic multi-stage grinding pair and the crushing rate, crushing heat and fracture time is constructed.Then a multi-objective optimization method of structural parameters of bionic multi-stage grinding pair is proposed to achieve the integration of optimal structural parameters based on the dynamic surrogate model by hybrid addition points strategy and NSGA-II algorithm. The effectiveness of the design method is verified and analyzed by experiments.

Key words: grinding pair, bovine teeth, bionic design, structural optimization

中图分类号:

S233.5

王金栋, 吴展扬, 谢宇鸿. 基于牛牙几何特征的仿生研磨副结构协同设计[J]. 机械工程学报, 2024, 60(19): 212-224.

WANG Jindong, WU Zhanyang, XIE Yuhong. Collaborative Design of Bionic Grinding Pair Structure Based on Geometric Characteristics of Bovine Teeth[J]. Journal of Mechanical Engineering, 2024, 60(19): 212-224.

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