Registration and fusion of aircraft lightning damage NDE data
department or school: Applied Science, Faculty of
department or school: Engineering, School of (Okanagan)
data provider: DSpace
degree campus: UBCO
creator: Fan, Yanshuo
issued: 2023-08-21T20:57:40Z
issued: 2023
related degree: Master of Applied Science - MASc
degree grantor: University of British Columbia
description: Lightning strikes are a critical concern for aircraft safety, necessitating the evaluation and maintenance of aircraft surface materials after each lightning event. Non-destructive evaluation/testing/inspection (NDE/NDT/NDI) methods play a vital role in assessing the structural condition of aircraft during maintenance procedures. However, each NDE technique has strengths and limitations when evaluating the stroked material. Therefore, the research in the thesis introduces novel image registration and fusion techniques that aim to overcome the limitations of individual NDE techniques and provide a comprehensive approach to aircraft material assessment. First, a structurally enhanced NDE image registration model is proposed, which can automatically align NDE images with ground-truth images. With the structural enhancement filter, the registration accuracy improves significantly. Compared to existing advanced models, the proposed model achieves reliable and consistent alignment results on multimodal NDE images without training. Then, a two-stage image fusion-translation network (FTnet) is proposed. This network combines an image fusion module with an image translation module to enhance the quality of the fused images. The fusion module employs a novel fusion strategy that yields excellent results despite its simple structure. Moreover, the image translation module optimizes the resulting image representation without requiring additional training. The fused images demonstrate a remarkable enhancement of the image information. FTnet surpasses existing methods without relying on large datasets. The model signifies its substantial advantages in the field of image fusion. The most remarkable advantage of the proposed models is their ability to provide reliable and efficient results in real industries with less reliance on large datasets. This makes these models more practical in the industry, where obtaining large amounts of data is challenging. Thus, the proposed models pr…
aggregated CHO: https://circle.library.ubc.ca/rest/handle/2429/85556
note: REGISTRATION AND FUSION OFAIRCRAFT LIGHTNING DAMAGENDE DATAbyYanshuo FanB.Sc., The University of Post and Telecommunication, 2017A THESIS SUBMITTED IN PARTIAL FULFILLMENT OFTHE REQUIREMENTS FOR THE DEGREE OFMASTER OF APPLIED SCIENCEinTHE COLLEGE OF GRADUATE STUDIES(Electrical Engineering)THE UNIVERSITY OF BRITISH COLUMBIA(Okanagan)August 2023© Yanshuo Fan, 2023The following individuals certify that they have read, and recommendto the College of Graduate Studies for acceptance, a thesis/dissertation en-titled:REGISTRATION AND FUSION OF AIRCRAFT LIGHTNINGDAMAGE NDE DATAsubmitted by Yanshuo Fan in partial fulfilment of the requirements of thedegree of Master of Applied ScienceDr. Zheng Liu, School of EngineeringSupervisorDr. Liwei Wang, School of EngineeringSupervisory Committee MemberDr. Peyman Yousefi, School of EngineeringSupervisory Committee MemberDr. Yang Cao, School of EngineeringUniversity ExamineriiAbstractLightning strikes are a critical concern for aircraft safety, necessitatingthe evaluation and maintenance of aircraft surface materials after each light-ning event. Non-destructive evaluation/testing/inspection (NDE/NDT/NDI)methods play a vital role in assessing the structural condition of aircraft dur-ing maintenance procedures. However, each NDE technique has strengthsand limitations when evaluating the stroked material. Therefore, the re-search in the thesis introduces novel image registration and fusion tech-niques that aim to overcome the limitations of individual NDE techniquesand provide a comprehensive approach to aircraft material assessment.First, a structurally enhanced NDE image registration model is pro-posed, which can automatically align NDE images with ground-truth im-ages. With the structural enhancement filter, the registration accuracy im-proves significantly. Compared to existing advanced models, the proposedmodel achieves reliable and consistent alignment results on multimodal NDEimages without training.Then, a two-stage image fusion-tra…
has type: Thesis/Dissertation
date issued: 2023-09
is shown at: 10.14288/1.0435505
language: eng
degree discipline: Electrical Engineering
provider: Vancouver : University of British Columbia Library
publisher: University of British Columbia
rights: Attribution-NonCommercial-NoDerivatives 4.0 International
rights URI: http://creativecommons.org/licenses/by-nc-nd/4.0/
scholar level: Graduate
contributor: Liu, Zheng (Professor of engineering)
type: Text
identifier URI: http://hdl.handle.net/2429/85556