摘要
针对基于几何约束自动识别的零部件精确定位技术中存在的识别效率和准确性不高的问题,提出了一种分层的几何约束自动识别方法。该方法通过装配意图获取、约束优先级判断、约束类型匹配、约束参数匹配、约束位置匹配和约束有效性检查等分层判断机制,有效地提高了几何约束自动识别的效率和准确性。相关方法已经在虚拟装配工艺规划系统中进行了验证,并已应用到航天产品的虚拟装配工艺规划中。
To deal with low efficiency and veracity of the automatic geometry constraint recognition technology, a multi-layer automatic geometry constraint recognition algorithm was proposed. Multi-layer measurement schemes such as assembly intent acquisition, constraint precedence judge, constraint type attribute matching, constraint parameter matching, destination position matching and constraint validity checking were adopted to improve the automatic geometry constraint recognition's efficiency and veracity very well. The proposed algorithm have been verified in the self-developed system named Virtual Assembly Process Planning(VAPP) System, and this VAPP system has been applied in assembly process planning of aerospace products.
出处
《计算机集成制造系统》
EI
CSCD
北大核心
2005年第4期498-502,共5页
Computer Integrated Manufacturing Systems
基金
"十五"总装预先研究资助项目(41318.1.1)~~
关键词
虚拟装配
约束识别
约束对象模型
精确定位
virtual assembly
constraint recognition
constraint object model
exact placement