Separating nut-shell pieces from hazelnuts and pistachio kernels using impact vibration analysis
Author
Habiboǧlu, Yusuf Hakan
Sevimli, Rasim Akın
Çetin, A. Enis
Pearson, T.C.
Date
2013Source Title
2013 21st Signal Processing and Communications Applications Conference (SIU)
Publisher
IEEE
Language
Turkish
Type
Conference PaperItem Usage Stats
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Abstract
In this article nut-shell pieces are separated from pistachio kernels and hazelnut kernels using impact vibration analysis. Vibration signals are recorded and analyzed in real-time. Mel-kepstral feature parameters and line spectral frequency values are extracted from the vibration signals. Feature parameters are classified using a Support Vector Machine (SVM) which was trained a priori using a manually classified data set. An average classification rate of 96:3% and 98:3%was achieved with Antepstyle Turkish pistachio nuts and hazelnuts. An important feature of the method is that it is easily trainable for other kinds of pistachio nuts and other nuts including walnuts. © 2013 IEEE.
Keywords
Impact vibration analysisLine spectral frequencies
Mel-kepstral feature
Classification rates
Data set
Feature parameters
Important features
Line spectral frequencies
Mel-kepstral feature
Pistachio nut
Vibration signal
Signal encoding
Support vector machines
Vibration analysis