• Korean Journal of Computational Design and Engineering
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• v.18 no.2
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• pp.113-119
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• 2013

This paper proposes an approach to detect unintended deflections in an automotive outer panel. Conventionally, the detection of unintended deflections has been performed by experienced works, and it requires much amount of time and efforts. The motivation of this work is to reduce such efforts by providing an automated detection methodology. For the detection of unintended deflections, we make use of the measured data from an optical scanner which can be considered as a Z-map data. The proposed approach consists of four major steps; 1) measured data acquisition for an automotive outer panel, 2) identification of shape features, 3) removal of shape features, and 4) detection of unintended deflections via curvature analysis.