Computer Integrated Manufacturing System ›› 2021, Vol. 27 ›› Issue (1): 53-62.DOI: 10.13196/j.cims.2021.01.004

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AR guidance-based visual inspection method for cable laying quality consistency check

  

  • Online:2021-01-31 Published:2021-01-31
  • Supported by:
    Project supported by the Shanghai Aerospace Science and Technology Corporation,China(No.UACAST2015-17),and the National Natural Science Foundation,China(No.51975362)。

面向AR辅助引导的线缆敷设质量一致性视觉检测方法

刘睿1,尹旭悦1,范秀敏1,2+,王磊3,何其昌1   

  1. 1.上海交通大学机械与动力工程学院智能制造与信息工程研究所
    2.上海市网络化制造与企业信息化重点实验室
    3.上海航天精密机械研究所
  • 基金资助:
    上海航天技术研究院—上海交大航天先进技术联合研究中心资助项目(UACAST2015-17),国家自然科学基金资助项目(51975362)。

Abstract: Aerospace cables' laying quality directly exerts great influence on products properties.To make cable assembly quality meets consistency requirements,a cable laying quality check method based on head-mounted depth visual information and Augumented Reality (AR) warning technique with assembly process guidance content were proposed.Cable target image was segmented according to the manual assembly characteristics,then the skeleton information of cable target image was combined with its depth information to evaluate cable bending extent.Local feature of cable laying image was extracted and utilized for image matching,which estimated the orientation consistency of cable laying.A product information model for cable laying process detection was proposed to provide triggering evidence and guidance content in AR assistance system.AR-based visual inspection system for cable laying quality consistency check was developed and proved effectively with a simulated electronic module for cable assembly.

Key words: cable laying, quality consistency, augumented reality guidance, visual inspection

摘要: 航天线缆的敷设质量直接影响产品整机性能的发挥,为解决线缆手工敷设工艺一致性问题,提出了基于头戴式深度视觉信息的线缆敷设质量实时检测和工艺引导信息的增强现实(AR)推送方法。基于手工装配特点分割线缆目标图像,获得了线缆图像二维骨架及深度信息,评估线缆弯曲程度;提取了线缆敷设现场图像局部特征子,并进行了图像特征匹配,评估了线缆敷设走向;建立了用于线缆敷设过程检测与引导的产品信息模型,提供了检测判断依据和AR引导信息。开发了基于AR技术的线缆敷设质量一致性视觉检测系统,并通过模拟圆筒电子舱线缆敷设案例,验证了方法的可行性和有效性。

关键词: 线缆敷设, 质量一致性, 增强现实引导, 视觉检测

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