A case study of image data processing in automated ultrasonic testing based aerospace composites inspection

Guojin Feng, Jiangtao Sun, Alvin Yung Boon Chong, Jamil Kanfoud, Tat Hean Gan, M. Kimball, M. Al Rashed, L. M. Vega, A. Garcia, G. S. Virk

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


Composite materials have gained increasingly wide use in many sectors such as aerospace and wind turbine systems, due to inherent physical and structural qualities that are not readily achievable with traditional materials. Inspecting material integrity is mandatory for safety and effective performance and ultrasonic testing has been recognised as an effective non-destructive technique for detecting internal defects in many different materials, including composites. The InnovateUK funded AutoDISC project is investigating automated ultrasonic inspection of aerospace composites with enhanced defect detection, aided by gantry-deployed robotic tools. This paper presents details of the robotic sensors and associated signal and image data processing of aerospace structures such as aircraft wings and fuselages. A robust robotic system has been developed to accurately deploy sensors that are able to react to a structure's varying surface height and curvature. The autonomy of the scanning system is being explored to allow specific features identified as important to be followed in the inspection process. A curved glass fibre reinforced polymer (GFRP) sample with simulated defects is inspected by the automated system. Analysis of experimental results shows that the simulated defects can be identified with a proper combination of techniques, including local gating, Gaussian low-pass filter, thresholding and morphological filter. On this basis, an interactive graphical user interface (GUI) is designed to aid analysis of the large three-dimensional data set and to determine processing parameters, such as gating window, threshold method and filter parameters, for subsequent automated defect recognition.
Original languageEnglish
Title of host publication1st World Congress on Condition Monitoring (WCCM 2017)
PublisherBritish Institute of Non-Destructive Testing
Number of pages12
ISBN (Print)9781510844759
Publication statusPublished - 1 Oct 2017
Externally publishedYes
Event1st World Congress on Condition Monitoring - ILEC Conference Centre, London, United Kingdom
Duration: 13 Jun 201716 Jun 2017
http://www.bindt.org/events/PastEvents/WCCM-2017/ (Link to Conference Website)


Conference1st World Congress on Condition Monitoring
Abbreviated titleWCCM 2017
Country/TerritoryUnited Kingdom
Internet address


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