Home Acta Aeronautica et Astronautica Sinica Article
PDF (2 MB)
Cite
EndNote(RIS) BibTeX
Collect
Submit Manuscript
Show Outline
Outline
Abstract
Keywords
References
Show full outline
Hide outline
Publishing Language: Chinese

A digital twin testing and adjusting system for aero-engine casings based on augmented reality

Yingjie MEI1,2, Dawei WANG1,2, Chuanzhi SUN1,2, Lamei YUAN3, Xiaoming WANG1,2, Yongmeng LIU1,2()
Center of Ultra-Precision Optoelectronic Instrument Engineering, School of Instrumentation Science and Engineering, Harbin Institute of Technology, Harbin 150080, China
Key Lab of Ultra-Precision Intelligent Instrumentation Engineering, Ministry of Industry and Information Technology, Harbin Institute of Technology, Harbin 150080, China
School of Mathematics, Harbin Institute of Technology, Harbin 150080, China
Show Author Information

Abstract

In order to improve the assembly accuracy and efficiency of aero-engine casings, this paper proposes a digital twin testing and adjusting system for aero-engine casings based on augmented reality. Utilizing the high fidelity interactive characteristics of augmented reality device, real-time visualization guided assembly of multi-stage aero-engine casings is carried out. Furthermore, this paper establishes a mathematical model for the assembly of aero-engine multi-stage casings to achieve accurate prediction of coaxiality of multi-stage casing assembly. Combining the assembly mathematical model with visual models, this paper conducts digital twin assembly experiments based on simulated multi-stage aero-engine casings, to achieve digital twin model mapping for aero-engine casings. The experimental results show that the coaxiality prediction error of the digital twin assembly system proposed in this paper is 0.6 μm, the average latency of augmented reality visualization interaction is 11 ms, the average frame rate is 45 fps, and the assembly consumption time is reduced by 5 h, effectively improving the accuracy and efficiency of aero-engine casing assembly.

Keywords

aero-engineassembly of casingsdigital twinaugmented realityassembly mathematical modelvisualization mode
CLC number: V235.1 Document code: A Article ID: 1000-6893（2024）21-629462-13

References

[1]
ZHAO G, LI J Y, XU M C, et al. Overview and prospect of key assembly technologies for aero-engines[J]. Acta Aeronautica et Astronautica Sinica, 2022, 43（10）: 527484（in Chinese）.
Google Scholar
[2]
SUN H B, YAN J X, WEI X H, et al. Digital twin driven aero-engine assembly technology[J]. China Mechanical Engineering, 2020, 31（7）: 833-841（in Chinese）.
Google Scholar
[3]
GAO Y C. Research on assembly accuracy prediction and phase optimization methods for aeroengine rotors[D]. Dalian: Dalian University of Technology, 2020: 1-14（in Chinese）
[4]
ZHANG M W, LIU Y M, WANG D W, et al. A coaxiality measurement method for the aero-engine rotor based on common datum axis[J]. Measurement, 2022, 191: 110696.
Crossref Google Scholar
[5]
LI M H, WANG Y L, SUN Q C, et al. Assembly accuracy prediction and optimization of aero-engine rotor under the separation condition of assembly and measurement[J]. International Journal of Advanced Manufacturing Technology, 2022, 120: 3103-3112.
Crossref Google Scholar
[6]
TAYLOR HOPSON. 500H series roundness tester[J]. Sensor World, 2014, 20（8）: 44（in Chinese）.
Google Scholar
[7]
CHEN K, TANG X L, YE F, et al. Research on simulation and prediction of aeroengine rotor assembly process[J]. Chinese Journal of Turbomachinery, 2021, 63（1）: 72-78（in Chinese）.
Google Scholar
[8]
ZHOU T Y, GAO H. Modeling and simulation of the assembly accuracy of aero-engine rotors in the docking processes using a specially designed novel multi-DOF NC motion platform[J]. Aerospace Science and Technology, 2021, 113: 106648.
Crossref Google Scholar
[9]
KLOCKE F, VESELOVAC D, AUERBACH T, et al. Intelligent assembly for aero engine components[C]∥International Conference on Intelligent Robotics and Applications. 2008: 927-935.
Crossref
[10]
MEI S, LU J, XIE L X, et al. Prediction and improvement of concentric deviation transmission in compressor test pieces and casings[J]. Aerospace Precision Manufacturing Technology, 2023, 59（2）: 24-27（in Chinese）.
Google Scholar
[11]
MU X K, YUAN B, WANG Y L, et al. Novel application of mapping method from small displacement torsor to tolerance: Error optimization design of assembly parts[J]. Proceedings of the Institution of Mechanical Engineers Part B-Journal of Engineering Manufacture, 2022, 236（6-7）: 955-967.
Crossref Google Scholar
[12]
DENG W Q, MO R, CHEN K, et al. Prediction of assembly clearance of aeroengine rotor tip based on measured data[J]. Journal of Aerospace Power, 2022, 37（6）: 1273-1283（in Chinese）.
Google Scholar
[13]
LI M H. Geometric accuracy testing and prediction of aeroengine rotor assembly[D]. Dalian: Dalian University of Technology, 2022: 39-58（in Chinese）.
[14]
MU X K, WANG Y L, YUAN B, et al. A new assembly precision prediction method of aeroengine high-pressure rotor system considering manufacturing error and deformation of parts[J]. Journal of Manufacturing Systems, 2021, 61: 112-124.
Crossref Google Scholar
[15]
LI C T. Research on intelligent assembly method for aeroengine rotors based on deep learning[D]. Harbin: Harbin Institute of Technology, 2020: 1-7（in Chinese）.
[16]
LI J J, ZHOU G H, ZHANG C. A twin data and knowledge-driven intelligent process planning framework of aviation parts[J]. International Journal of Production Research, 2022, 60（17）: 5217-5234.
Crossref Google Scholar
[17]
HAN D M. Research on 3D Tracking and registration technology for aeroengine in hybrid reality[D]. Deyang: China Civil Aviation Flight Academy, 2022: 1-9（in Chinese）.
[18]
ZHANG Y Z, SUN H B, ZHOU P, et al. Dynamic prediction and regulation of assembly gap of rotary stator driven by digital twins[J]. Computer Integrated Manufacturing System, 2023, 29（6）: 2035-2046（in Chinese）.
Google Scholar
[19]
GREGORIO J L, LARTIGUE C, THIEBAUT F, et al. A digital twin-based approach for the management of geometrical deviations during assembly processes[J]. Journal of Manufacturing Systems, 2021, 58: 108-117.
Crossref Google Scholar
[20]
DING Z K, SUN Y C, DUAN L L, et al. Augmented reality multi person collaborative assembly based on digital twins[J]. Computer Integrated Manufacturing Systems, 2023, 29（6）: 2019-2034（in Chinese）.
Google Scholar
[21]
YUAN X, WANG H K, ZHAO K S, et al. Research and implementation of a gas turbine assembly guidance system based on augmented reality technology[J] Thermal Power Engineering, 2022, 37（S1）: 48-53（in Chinese）.
Google Scholar
[22]
MARINO E, BARBIERI L, COLACINO B, et al. User-centered design of an augmented reality tool for smart operator in production environment[C]∥Design Tools and Methods in Industrial Engineering II（ADM）. 2022: 125-132.
Crossref
[23]
LI Y, LIU Y, SUN C, et al. A geometric modeling method based on configuration space theory[J]. Mechanical Design and Manufacturing, 2005（5）: 54-56（in Chinese）.
Google Scholar
[24]
SAC. Geometrical Product Specifications（GPS）geometric tolerances for shape, direction, position, and runout tolerances: GB/T 1182-2018[S]. Beijing: Standards Press of China, 2018（in Chinese）.
[25]
BESL P J, MCKAY N D. A method for registration of 3-D shapes[J]. Proceedings of SPIE - The International Society for Optical Engineering, 1992, 14（3）: 239-256.
Crossref Google Scholar
[26]
MEI Y J, SUN C Z, LI C T, et al. Research on intelligent assembly method of aero-engine multi-stage rotors based on SVM and variable-step AFSA-BP neural network[J]. Advanced Engineering Informatics, 2022, 54: 101798.
Crossref Google Scholar
[27]
SUN C Z. Research on multistage rotor coaxiality measurement method based on vector projection[D] Harbin: Harbin Institute of Technology, 2017: 21-40（in Chinese）.
Acta Aeronautica et Astronautica Sinica
Volume 45 Issue 21,
November 2024
Article number: 629462
DOI: 10.7527/S1000-6893.2023.29462
Cite this article:
MEI Y, WANG D, SUN C, et al. A digital twin testing and adjusting system for aero-engine casings based on augmented reality. Acta Aeronautica et Astronautica Sinica, 2024, 45(21): 629462. https://doi.org/10.7527/S1000-6893.2023.29462
Metrics & Citations  
Article History
Copyright
Return