摘要
为解决产品改造升级复杂度高、拆卸难度大等问题,在机电产品设计阶段引入影响产品改造升级相关因素,提出一种考虑改造升级风险的复杂产品模块智能聚类方法。从产品零部件的功能相关性、结构相关性、关联更改概率、拆卸相关性等方面定义零部件关联属性,建立产品零部件间综合关联矩阵;采用结合改进人工蜂群算法的密度峰值聚类算法求解模块划分方案,以模块划分质量为优化目标,实现截断距离的优选。以某型号升降电梯的零部件模块划分为例,验证了所提方法的可行性和有效性。
In order to solve the problems of high complexity of product transformation and upgrading and difficulty in disassembly,related factors affecting product transformation and upgrading are introduced in the design stage of mechanical and electrical products,and an intelligent clustering method for complex product modules considering the risk of transformation and upgrading is proposed.From the functional correlation,structural correlation,associated change probability,disassembly correlation,etc.of product parts and components,the association attributes of parts are defined,and a comprehensive association matrix between product parts is established,the density peak clustering algorithm combined with improved artificial bee colony algorithm is used to solve the module partition scheme.Taking the quality of module partition as the optimization objective,the optimization of truncation distance parameters is realized.Finally,the elevator module partition is taken as an example to verify the effectiveness of the method.
作者
张芹
潘金龙
洪兆溪
Zhang Qin;Pan Jinlong;Hong Zhaoxi(College of Mechanical-Electronic and Automobile Engineering,Huzhou Vocatinal & Technical College,Zhejiang Huzhou,313000,China;Shanghai Space Propulsion Technology Research Institute,Shanghai,201109,China;State Key Labratory of Fluid Power Transmission and Control,Zhejiang University, Zhejiang Hangzhou,310027,China)
出处
《机械设计与制造工程》
2022年第5期6-12,共7页
Machine Design and Manufacturing Engineering
基金
国家重点研发计划资助项目(2020YFB1711700)
湖州市自然科学基金资助项目(2019YZ09)
浙江省访问工程师校企合作项目(FG2021150)。
关键词
改造升级
密度峰值聚类算法
改进人工蜂群算法
模块划分
upgrading
density peak clustering algorithm
improved artificial bee colony algorithm
module partition
