Automatic characterization of surface-breaking crack defects in pipe walls using ultrasound images

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dc.contributor.authorGovor, Vladislav
dc.contributor.supervisorRakhmatov, Daler N.
dc.date.accessioned2025-04-29T20:46:40Z
dc.date.available2025-04-29T20:46:40Z
dc.date.issued2025
dc.degree.departmentDepartment of Electrical and Computer Engineering
dc.degree.levelMaster of Applied Science MASc
dc.description.abstractUltrasound imaging is a widely used technique in non-destructive testing for detecting and sizing defects in industrial pipelines. Accurate defect localization and sizing are critical for diagnosing the structural integrity of pipelines and preventing failures that pose significant environmental, economic, and safety risks. Motivated by the need to mitigate such risks, this thesis presents an effective technique for localization and sizing of surface-breaking cracks on the outer walls of liquid-filled pipes. The proposed approach combines traditional and novel data processing techniques applied to a sequence of multi-view ultrasound image frames of inspected pipe sections. Tri-sectional sliding windows are utilized for frame-by-frame view-specific defect localization, followed by establishing correspondence among potentially differing crack location estimates across all considered views and frames, as well as for defect sizing. Additionally, a similarity-based sizing method is developed to increase the accuracy by comparing synthetic images to the original ones. Our evaluation results using real-world experimental data demonstrate that the sliding window method is computationally inexpensive and yields accurate localization and sizing results in most cases, while the similarity-based method provides superior sizing accuracy in more complex scenarios.
dc.description.embargo2026-04-24
dc.description.scholarlevelGraduate
dc.identifier.urihttps://hdl.handle.net/1828/22045
dc.languageEnglisheng
dc.language.isoen
dc.rightsAvailable to the World Wide Web
dc.subjectCrack sizing
dc.subjectUltrasound
dc.subjectSurface-breaking cracks
dc.subjectCrack localization
dc.subjectComputer vision
dc.subjectNon-destructive testing
dc.subjectCrack characterization
dc.subjectPipelines
dc.titleAutomatic characterization of surface-breaking crack defects in pipe walls using ultrasound images
dc.typeThesis

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