• Libraries
    • Log in to:
    View Item 
    •   MSpace Home
    • Faculty of Graduate Studies (Electronic Theses and Practica)
    • FGS - Electronic Theses and Practica
    • View Item
    •   MSpace Home
    • Faculty of Graduate Studies (Electronic Theses and Practica)
    • FGS - Electronic Theses and Practica
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Vision-guided robotic abrasion and water-break inspection of free-form composite panels

    View/Open
    Thesis (3.776Mb)
    Date
    2022-08-22
    Author
    Dharia, Bhavin
    Metadata
    Show full item record
    Abstract
    Carbon fiber and fiberglass composite panels are commonly used in the aerospace and automotive industries. During the manufacturing process, composite panels undergo surface treatment processes such as priming and coating. For coating layers to adhere strongly to the surface, the part surface must be free of any contamination such as grease. Detection and removal of contamination is an important step in the manufacturing of composite panels, particularly in the aerospace industry. This thesis develops a novel vision-based framework to enable fully automated inspection and robotic abrasion of free-form composite panels. The first aim of the thesis is to automatically locate arbitrarily placed composite panels within the robot workplace. The proposed method employs iterative closest point (ICP) registration technique for locating the part in the robot cell. An additional module based on vision-based error correction is developed in the thesis for improving the accuracy of part localization. The proposed part localization technique eliminates the need for manual calibration of part placement in each robot cycle. The ASTM-F22 water-break test is widely used for detecting hydrophobic contamination on a surface. As the second aim in this thesis, vision-based algorithms are developed to allow for the automated detection (inspection) of hydrophobic contamination during the water-break test. The developed vision-based algorithms can successfully detect the layer of hydrophobic contamination on the free-form panel. The third aim of this thesis is to automatically generate robotic abrasion tool paths to remove detected contamination. In the proposed framework, the panel surface is divided into multiple grids. The point clouds of each grid are first used to reconstruct continuous parametric B-spline surfaces. B-spline surfaces are then used to make an abrasion tool path for each grid. The developed vision-based inspection algorithm determines which grids contain contamination and therefore must be abraded. To conclude, the overarching goal of this thesis is to develop a fully automated vision-based framework for the detection and removal (robotic abrasion) of contamination on free-form composite panels. The developed techniques have been successfully implemented and verified on a Kuka KR6 industrial robot equipped with 2D and 3D vision cameras.
    URI
    http://hdl.handle.net/1993/36755
    Collections
    • FGS - Electronic Theses and Practica [25529]
    • Manitoba Heritage Theses [6064]

    DSpace software copyright © 2002-2016  DuraSpace
    Contact Us | Send Feedback
    Theme by 
    Atmire NV
     

     

    Browse

    All of MSpaceCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

    My Account

    Login

    Statistics

    View Usage Statistics

    DSpace software copyright © 2002-2016  DuraSpace
    Contact Us | Send Feedback
    Theme by 
    Atmire NV