Separating nut-shell pieces from hazelnuts and pistachio kernels using impact vibration analysis
Date
2013
Advisor
Instructor
Source Title
2013 21st Signal Processing and Communications Applications Conference (SIU)
Print ISSN
Electronic ISSN
Publisher
IEEE
Volume
Issue
Pages
Language
Turkish
Type
Conference Paper
Journal Title
Journal ISSN
Volume Title
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.
Course
Other identifiers
Book Title
Keywords
Impact vibration analysis, Line 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