Intelligent detection and AR guidance of aero-engine blade assembly execution process

被引：0
|
作者：
Zhang L. [1 ]
Wang S. [1 ]
He W. [1 ]
Li J. [1 ]
Moj S. [1 ]
Wei B. [1 ]
Wang M. [2 ]
机构：
[1] School of Mechanical Engineering, Northwestern Polytcchnical University, Xi'an
[2] Aecc Xi'an Aero-Engine Ltd., Xi'an
来源：
Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS | 2024年 / 30卷 / 04期
关键词：
acro-cnginc blade; assembly execution process; augmented reality; optical character recognition; post-processing;
D O I：
10.13196/j.cims.2022.0945
中图分类号：
学科分类号：
摘要：
To improve the intelligence level of the acro-cnginc blade assembly execution process, a method for intelligent detection and AR guidance of the acro-cnginc blade assembly execution process was proposed, which included three links: blade coding recognition, material kitting based on AR and status detection during the complete placement process. To solve the problem of lack of automatic identification and intelligent error correction, an acro-cnginc blade material management architecture based on codcrccognition was built, and an image processing based on preprocessing enhancement for blade codcimages was proposed. Baycsian error correction was used to judge the recognition results and perform post-processing for error correction, which improved the recognition accuracy of blade codes. Meanwhile, in the process of manual material kitting, AR enhanced visual information was used to assist users in quickly executing task tasks, reducing the time for selecting blade materials. In addition, an error prevention and correction system based on detection and comparison was built for blade material placement, which could avoid human errors. The intelligent detection and AR guidance method proposed for acro-cnginc blade assembly execution process could effectively reduce the consumption of human, material resources and time, which played a technical supporting role in promoting the acro-cnginc towards intelligent and automatic production. © 2024 CIMS. All rights reserved.
引用
收藏
页码：1263 / 1272
页数：9
相关论文
共 26 条
  • [1] SUN Huibin, CHANG Zhiyong, Study on complex product assembly executive process modeling and monitoring method, China Mechanical Engineering, 20, 16, pp. 1947-1951, (2009)
  • [2] LI J, HUANG T, YANG Y, Et al., Detection and recognition of characters on the surface of metal workpieces with complex background, Proceedings of 2020 IEEE 4th Information Technology , Networking, Electronic and Automation Control Conference (ITNEC), pp. 2236-2240, (2020)
  • [3] DE KOSTER R, LE-DUC T, ROODBERGEN K J., Design and control of warehouse order picking: A literature review[J], European Journal of Operational Research, 182, 2, pp. 481-501, (2007)
  • [4] GROSSE E H, GLOCK C, JABER M Y, Et al., Incorporating human factors in order picking planning models
  • [5] framework and research opportunities, International Journal of Production Research, 53, 3, pp. 695-717, (2015)
  • [6] LIANG Shengtao, CHEN Liangkun, SHU Qiqi, Et al., Design of intelligent storage system based on wireless communication and RFID positioning[J], Techniques of Automation and Applications, 39, 1, pp. 169-172, (2020)
  • [7] SELVARAJ AS, ANUSHA S., RFID enabled smart data a-nalysis in a smart warehouse monitoring system using IoT[J], Journal of Physics Conference Series, 1717, (2021)
  • [8] DU Xiaoming, GE Shilun, Research for medium and small enterprises warehouse management system in RFID and bar ode[J], Modular Machine Tool 6- Automatic Manufacturing, 2, pp. 106-109
  • [9] HU Shenghai, LI Qiyue, LIU Zaichun, Et al., New intelligent ounter design and application [ J ], Applied Science and Tech-lology, 38, 5, pp. 13-17, (2011)
  • [10] YEOW PHP, GOOMAS D T., Ergonomics improvement in order election in a refrigerated environment, Human Factors and Ergonomics in Manufacturing o- Service Industries, 24, 3, pp. 262-274, (2014)
123