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基于层次聚类算法的大型玉米收获机械模块划分方法
引用本文:毛恩荣,马静仪,杜岳峰,朱忠祥,翟志强.基于层次聚类算法的大型玉米收获机械模块划分方法[J].中国农业大学学报,2022,27(5):73-85.
作者姓名:毛恩荣  马静仪  杜岳峰  朱忠祥  翟志强
作者单位:中国农业大学 现代农业装备优化设计北京市重点实验室, 北京 100083
基金项目:国家重点研发计划(2020YFB1713502);国家重点研发计划(2017YFD0700101)
摘    要:针对大型玉米收获机械传统设计模式研发周期长,设计成本高等问题,采用分层次模块划分方法,对玉米收获机械进行功能划分,将总功能分解为一级功能、二级功能和功能载体,建立产品的功能主结构后,将整机划分为9个功能模块;基于功能-装配-能量接口关系,提出了部件层的模块划分原则,通过零部件之间的功能关系、装配关系、能量-接口关系建立加权模糊矩阵,将抽象的连接关系映射为具体化的关联矩阵,采用层次聚类算法求解关联矩阵,将9个功能模块细分为186个二级模块和645个子模块,从而实现了玉米收获机部件层零部件模块的精确划分。为实现该模块划分方法的工程应用,基于Qt Creator平台,开发大型玉米收获机械模块化快速设计系统,该系统可完成模块划分、模块管理和基于用户需求的模块配置等功能,从而实现大型玉米收获机械的快速设计。与传统玉米收获机械设计方法相比,应用模块划分方法可显著提升大型玉米收获机械设计效率,缩短整机产品的开发周期。

关 键 词:模块划分  玉米收获机  层次聚类  快速设计
收稿时间:2021/9/26 0:00:00

Module division method of large corn harvester based on hierarchical clustering algorithm
MAO Enrong,MA Jingyi,DU Yuefeng,ZHU Zhongxiang,ZHAI Zhiqiang.Module division method of large corn harvester based on hierarchical clustering algorithm[J].Journal of China Agricultural University,2022,27(5):73-85.
Authors:MAO Enrong  MA Jingyi  DU Yuefeng  ZHU Zhongxiang  ZHAI Zhiqiang
Institution:Beijing Key Laboratory of Optimized Design for Modern Agricultural Equipment, China Agricultural University, Beijing 100083, China
Abstract:In view of the problems of long research and development cycle and high design cost in traditional large-scale corn harvester design mode, the function division of corn harvester is conducted by using the hierarchical module division method. The overall functions are decomposed into primary functions, secondary functions and functional carriers. After the main product structure is established, the whole machine is divided into nine functional modules. Based on the nine functional modules, the module division principle based on the interface relationship of function-assembly-energy is proposed. The weighted fuzzy matrix is established through the functional relation, assembly relation and energy-interface relation among components, and the abstract relation is mapped into concrete association matrix. By solving the incidence matrix with hierarchical clustering algorithm, the nine functional modules are subdivided into several sub-modules, and the precise division of component modules at component level is realized. Based on Qt Creator platform, a modular rapid design system for large-scale corn harvester, which can complete the functions of module division, module management and module configuration according to the needs of user and realize the rapid design of large-scale corn harvester, is developed.
Keywords:module division  corn harvester  rapid design  hierarchical clustering
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