首页 | 本学科首页   官方微博 | 高级检索  
     

基于数字孪生的航天器装配质量监控与预测技术
引用本文:张佳朋,刘检华,龚康,张川,庄存波,赵本华.基于数字孪生的航天器装配质量监控与预测技术[J].计算机集成制造系统,2021,27(2):605-616.
作者姓名:张佳朋  刘检华  龚康  张川  庄存波  赵本华
作者单位:北京理工大学 机械与车辆学院,北京 100081;北京卫星制造厂有限公司,北京 100094;北京理工大学 机械与车辆学院,北京 100081;北京卫星制造厂有限公司,北京 100094;航天科工空间工程发展有限公司,湖北 武汉 100854;北京理工大学 机械与车辆学院,北京 100081;北京卫星制造厂有限公司,北京 100094
基金项目:装备预先研究资助项目;国防基础科研资助项目;国家自然科学基金资助项目
摘    要:鉴于航天器装配过程中不确定因素多,无法准确有效地预测和评估航天器的实际性能,装配过程中因进行大量复杂的性能试验来验证产品性能指标的符合性而极大影响了装配效率,提出一种基于数字孪生的航天器装配质量在线监控与预测方法。分析了航天器装配执行层面总体流程的特点,在此基础上给出面向航天器装配质量的数字孪生建模方法,以及面向数字孪生构建的产品监控与数据管理方法,最后提出一种基于灰度关联的装配过程质量综合预测方法,可用于航天器装配质量预测。以空间站某泵组件产品为实例,验证了所提方法的正确性。

关 键 词:数字孪生  航天器装配  质量监控  质量预测  数据管理

Spacecraft assembly quality control and prediction technology based on digital twin
ZHANG Jiapeng,LIU Jianhua,GONG Kang,ZHANG Chuan,ZHUANG Cunbo,ZHAO Benhua.Spacecraft assembly quality control and prediction technology based on digital twin[J].Computer Integrated Manufacturing Systems,2021,27(2):605-616.
Authors:ZHANG Jiapeng  LIU Jianhua  GONG Kang  ZHANG Chuan  ZHUANG Cunbo  ZHAO Benhua
Affiliation:(School of Mechanical Engineering,Beijing Institute of Technology,Beijing 100081,China;Beijing Spacecraft Co.,Ltd.,Beijing 100094,China;Sasicspace,Wuhan 100854,China)
Abstract:There are many uncertain factors in the assembly process of spacecraft,and the assembly personnel need to adjust the assembly strategy according to the changes at any time,which makes the final actual performance of spacecraft cannot be accurately and effectively predicted and evaluated.Therefore,a large number of complex performance tests were needed to verify the conformity of product performance indicators in the assembly process,which greatly affected the assembly efficiency.Aiming at the above problems,a method of spacecraft assembly quality online monitoring and prediction based on digital twin was proposed.The general process characteristics of spacecraft assembly execution level were analyzed.On this basis,the digital twin modeling method for spacecraft assembly quality and the product monitoring and data management method for digital twin construction were given.A comprehensive prediction method of assembly process quality based on gray correlation was proposed,which could be used for spacecraft assembly quality prediction.The correctness of the proposed method was verified by taking a pump component product of space station as an example.
Keywords:digital twin  spacecraft assembly  quality control  quality prediction  data management
本文献已被 CNKI 维普 万方数据 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号