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大型风洞设备的数智化初步研究

廖达雄 孙运强 吴静怡 彭磊

廖达雄,孙运强,吴静怡,等. 大型风洞设备的数智化初步研究[J]. 实验流体力学,2022,36(1):1-10 doi: 10.11729/syltlx20210072
引用本文: 廖达雄,孙运强,吴静怡,等. 大型风洞设备的数智化初步研究[J]. 实验流体力学,2022,36(1):1-10 doi: 10.11729/syltlx20210072
LIAO D X,SUN Y Q,WU J Y,et al. Digital intelligent technology research of large wind tunnel equipment[J]. Journal of Experiments in Fluid Mechanics, 2022,36(1):1-10. doi: 10.11729/syltlx20210072
Citation: LIAO D X,SUN Y Q,WU J Y,et al. Digital intelligent technology research of large wind tunnel equipment[J]. Journal of Experiments in Fluid Mechanics, 2022,36(1):1-10. doi: 10.11729/syltlx20210072

大型风洞设备的数智化初步研究

doi: 10.11729/syltlx20210072
基金项目: 空气动力学国家重点实验室创新基金(JBKYC190101)
详细信息
    作者简介:

    廖达雄:(1963—),男,浙江衢州人,研究员。研究方向:空气动力学地面试验设备设计和研究。通信地址:四川省绵阳市涪城区二环路南段6号12信箱(621000)。E-mail: liaodaxiong@cardc.cn

    通讯作者:

    E-mail: liaodaxiong@cardc.cn

  • 中图分类号: V211.7

Digital intelligent technology research of large wind tunnel equipment

  • 摘要: 数智化技术是大型风洞设备设计、建设与运行的重要内容和发展方向。对国内外大型风洞设计建设中的数字化、网络化和智能化技术研究现状进行了简要的梳理和总结;分析了当前大型风洞设备在设计建设过程中面临的数字化多学科协同设计、数据分析管理、数据交互与融合、智能制造与装配、健康管理、智能机器人等数智化技术问题及其发展趋势;提出了构建数智化风洞系统的设计思路。
  • 图  1  跨声速风洞槽壁试验段流场分布图[12]

    Figure  1.  Test section flow distribution of transonic wind tunnel[12]

    图  2  测控系统网络拓扑结构图[25]

    Figure  2.  Network topology of measurement and control system[25]

    图  3  风洞现场总线测控系统结构框图[26]

    Figure  3.  Structure diagram of field bus in wind tunnel[26]

    图  4  NF-6风洞压缩机状态监控系统[28]

    Figure  4.  Condition monitoring system of NF-6 wind tunnel compressor[28]

    图  5  基于HNC100的伺服控制模式原理图[37]

    Figure  5.  Schematic diagram of servo control mode based on HNC100[37]

    图  6  PIV流场测试系统[18]

    Figure  6.  Flow field measurement system of PIV[18]

    图  7  三种手段融合式发展

    Figure  7.  Integrated development of three means

    图  8  虚拟制造与装配[51]

    Figure  8.  Virtual manufacturing and assembly[51]

    图  9  NFT智能温度调节控制

    Figure  9.  Intelligent temperature control of NTF

    图  10  风洞智能状态监测及健康管理系统总体架构[12]

    Figure  10.  Overall structure of intelligent state detection and health management in wind tunnel[12]

    图  11  特殊环境中的智能机器人技术[52]

    Figure  11.  Intelligent robot technology in special environment[52]

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出版历程
  • 收稿日期:  2021-07-15
  • 修回日期:  2021-12-15
  • 录用日期:  2021-12-16
  • 刊出日期:  2022-03-17

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