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Proceedings Paper

Aircraft exterior scratch measurement system using machine vision
Author(s): Dennis P. Sarr
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Paper Abstract

In assuring the quality of aircraft skin, it must be free of surface imperfections and structural defects. Manual inspection methods involve mechanical and optical technologies. Machine vision instrumentation can be automated for increasing the inspection rate and repeatability of measurement. As shown by previous industry experience, machine vision instrumentation methods are not calibrated and certified as easily as mechanical devices. The defect must be accurately measured and documented via a printout for engineering evaluation and disposition. In the actual usage of the instrument for inspection, the device must be portable for factory usage, on the flight line, or on an aircraft anywhere in the world. The instrumentation must be inexpensive and operable by a mechanic/technician level of training. The instrument design requirements are extensive, requiring a multidisciplinary approach for the research and development. This paper presents the image analysis results of microscopic structures laser images of scratches on various surfaces. Also discussed are the hardware and algorithms used for the microscopic structures laser images. Dedicated hardware and embedded software for implementing the image acquisition and analysis have been developed. The human interface, human vision is used for determining which image should be processed. Once the image is chosen for analysis, the final answer is a numerical value of the scratch depth. The result is an answer that is reliable and repeatable. The prototype has been built and demonstrated to Boeing Commercial Airplanes Group factory Quality Assurance and flight test management with favorable response.

Paper Details

Date Published: 1 August 1991
PDF: 8 pages
Proc. SPIE 1472, Image Understanding and the Man-Machine Interface III, (1 August 1991); doi: 10.1117/12.46482
Show Author Affiliations
Dennis P. Sarr, Boeing Commercial Airplanes Group (United States)

Published in SPIE Proceedings Vol. 1472:
Image Understanding and the Man-Machine Interface III
Eamon B. Barrett; James J. Pearson, Editor(s)

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