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2007

Feasibility of impact-acoustic emissions for detection of damaged wheat kernels

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Feasibility of impact-acoustic emissions for detection of damaged wheat kernels
A non-destructive, real time device was developed to detect insect damage, sprout damage, and scab damage in kernels of wheat. Kernels are impacted onto a steel plate and the resulting acoustic signal analyzed to detect damage. The acoustic signal was processed using four different methods: modeling of the signal in the time-domain, computing time-domain signal variances and maximums in short-time windows, analysis of the frequency spectrum magnitudes, and analysis of a derivative spectrum. Features were used as inputs to a stepwise discriminant analysis routine, which selected a small subset of features for accurate classification using a neural network. For a network presented with only insect damaged kernels (IDK) with exit holes and undamaged kernels, 87% of the former and 98% of the latter were correctly classified. It was also possible to distinguish undamaged, IDK, sprout-damaged, and scab-damaged kernels. © 2005 Elsevier Inc. All rights reserved.
Tom C. Pearson, A. Enis Çetin, Ahmed H. Tew
Added 13 Dec 2010
Updated 13 Dec 2010
Type Journal
Year 2007
Where DSP
Authors Tom C. Pearson, A. Enis Çetin, Ahmed H. Tewfik, Ron P. Haff
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