Identifying sources of variation in horizontal stabilizer assembly using finite element analysis and principal component analysis

被引:28
|
作者
Wang, Hua [1 ]
Ding, Xin [2 ]
机构
[1] Shanghai Jiao Tong Univ, Shanghai Key Lab Digital Autobody Engn, Shanghai 200030, Peoples R China
[2] Sch Mech Engn, Shanghai, Peoples R China
基金
中国国家自然科学基金;
关键词
Assembly; Aerospace industry; Finite element analysis; Principal component analysis; TOLERANCE ANALYSIS; SIMULATION; DIAGNOSIS; COMPLIANT;
D O I
10.1108/01445151311294847
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Purpose - The purpose of this paper is to propose a method to identify sources of variation in horizontal stabilizer assembly using FEA (finite element analysis) and PCA (principal component analysis). Design/methodology/approach - The horizontal stabilizer is assembled by long and thin-walled deformable aluminum components. Part-to-part assembly of these compliant components regularly causes difficulties associated with dimensional variations. Finite element modeling and PCA are employed to predict the propagation of variation from edge to horizontal stabilizer. Findings - The variation analysis combined with pattern fitting method is demonstrated in a case study of the horizontal stabilizer assembly system and good performance is obtained. The results have shown that the FEA and PCA method has the capability of predicting, to an acceptable degree of accuracy, the overall geometrical variations propagation of the edges and trailing edge. Originality/value - The results of this research will enhance the understanding of the compliant components deformation in assembly, and help to systematically improve the precision control efficiency in civil aircraft assembly.
引用
收藏
页码:86 / 96
页数:11
相关论文
共 50 条
  • [11] Development of a Parametric Clavicle Finite Element Model Using Principal Component Analysis and Mesh Morphing Algorithm
    SHI Xiang-nan
    HE Yu-hao
    Chinese Journal of Biomedical Engineering, 2017, 26 (03) : 93 - 104
  • [12] Identifying differentiating characteristics of Internet applications using Principal Component Analysis
    Nogueira, Roberto
    Nogueira, Antonio
    Salvador, Paulo
    Valadas, Rui
    CSNDSP 08: PROCEEDINGS OF THE SIXTH INTERNATIONAL SYMPOSIUM ON COMMUNICATION SYSTEMS, NETWORKS AND DIGITAL SIGNAL PROCESSING, 2008, : 114 - +
  • [13] Identifying silica types using viscosity data and principal component analysis
    Nascimento, Harrison Henri dos Santos
    Nascimento, Marcio Luis Ferreira
    JOURNAL OF PHYSICS AND CHEMISTRY OF SOLIDS, 2021, 157
  • [14] Novel Method for Optimal Placement of Power System Stabilizer using Principal Component Analysis
    Kamalasadan, Sukumar
    Kulkarni, Nikhil
    2013 IEEE INDUSTRY APPLICATIONS SOCIETY ANNUAL MEETING, 2013,
  • [15] PRINCIPAL COMPONENT ANALYSIS - A TOOL FOR ASSEMBLY MANAGEMENT
    TADAYON, F
    LIU, MC
    COMPUTERS & INDUSTRIAL ENGINEERING, 1993, 25 (1-4) : 77 - 80
  • [16] PRINCIPAL COMPONENT ANALYSIS OF INFRASPECIFIC VARIATION IN BACTERIA
    DARLAND, G
    APPLIED MICROBIOLOGY, 1975, 30 (02) : 282 - 289
  • [17] The characteristics analysis of strain variation associated with Wenchuan earthquake using principal component analysis
    Zhu, Kaiguang
    Chi, Chengquan
    Yu, Zining
    Fan, Mengxuan
    Li, Kaiyan
    Sun, Huihui
    ANNALS OF GEOPHYSICS, 2020, 63 (05) : 1 - 12
  • [18] Anatomical Variation of the Tibia – a Principal Component Analysis
    Liselore Quintens
    Michiel Herteleer
    Sanne Vancleef
    Yannick Carette
    Joost Duflou
    Stefaan Nijs
    Jos Vander Sloten
    Harm Hoekstra
    Scientific Reports, 9
  • [19] Anatomical Variation of the Tibia - a Principal Component Analysis
    Quintens, Liselore
    Herteleer, Michiel
    Vancleef, Sanne
    Carette, Yannick
    Duflou, Joost
    Nijs, Stefaan
    Vander Sloten, Jos
    Hoekstra, Harm
    SCIENTIFIC REPORTS, 2019, 9 (1)
  • [20] Principal Component Analysis with Coefficient of Variation Matrix
    Kim, Ji-Hyun
    KOREAN JOURNAL OF APPLIED STATISTICS, 2015, 28 (03) : 385 - 392