Browsing by Subject "Impact vibration analysis"
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Item Open Access Separating nut-shell pieces from hazelnuts and pistachio kernels using impact vibration analysis(IEEE, 2013) Habiboǧlu, Yusuf Hakan; Sevimli, Rasim Akın; Çetin, A. Enis; Pearson, T.C.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.Item Open Access System for removing shell pieces hazelnut kernels using impact vibration analysis(Elsevier BV, 2014-02) Çetin, A. Enis; Pearson, T. C.; Sevimli, R. A.A system for removing shell pieces from hazelnut kernels using impact vibration analysis was developed in which nuts are dropped onto a steel plate and the vibration signals are captured and analyzed. The mel-cepstral feature parameters, line spectral frequency values, and Fourier-domain Lebesgue features were extracted from the vibration signals. The best experimental results were obtained using the melcepstral feature parameters. The feature parameters were classified using a support vector machine (SVM), which was trained a priori using a manually classified dataset. An average recognition rate of 98.2% was achieved. An important feature of the method is that it is easily trainable, enabling it to be applicable to other nuts, including walnuts and pistachio nuts. In addition, the system can be implemented in real time. 2013 Elsevier B.V. All rights reserved