An intelligent procedure for watermelon ripeness detection based on vibration signals

被引:27
作者
Abbaszadeh, Rouzbeh [1 ]
Moosavian, Ashkan [2 ]
Rajabipour, Ali [3 ]
Najafi, G. [2 ]
机构
[1] IROST, Agr Res Inst, Tehran, Iran
[2] Tarbiat Modares Univ, Dept Mech Engn Agr Machinery, Tehran, Iran
[3] Univ Tehran, Dept Agr Machinery, Fac Agr Engn & Technol, Coll Agr & Nat Resources, Karaj, Iran
来源
JOURNAL OF FOOD SCIENCE AND TECHNOLOGY-MYSORE | 2015年 / 52卷 / 02期
关键词
Watermelon; Ripeness detection; Laser Doppler vibrometry; Fast Fourier transform; Feature extraction; K-nearest neighbor; NONDESTRUCTIVE DETERMINATION; QUALITY EVALUATION; FEATURE-EXTRACTION; INTERNAL QUALITY; FAULT-DIAGNOSIS; SOLUBLE SOLIDS; LASER; CLASSIFICATION; TEXTURE; SPECTROSCOPY;
D O I
10.1007/s13197-013-1068-x
中图分类号
TS2 [食品工业];
学科分类号
0832 ;
摘要
In this paper, an efficient procedure for ripeness detection of watermelon was presented. A nondestructive method was used based on vibration response to determine the internal quality of watermelon. The responses of samples to vibration excitation were optically recorded by a Laser Doppler (LD) vibrometer. Vibration data was collected from watermelons of two qualities, namely, ripe and unripe. Vibration signals were transformed from time-domain to frequency-domain by fast Fourier transform (FFT). Twenty nine features were extracted from the FFT amplitude and phase angle of the vibration signals. K-nearest neighbor (KNN) analysis was applied as a classifier in decision-making stage. The experimental results showed that the usage of the FFT amplitude of the vibration signals gave the maximum classification accuracy. This method allowed identification at a 95.0 % level of efficiency. Hence, the proposed method can reliably detect watermelon ripeness.
引用
收藏
页码:1075 / 1081
页数:7
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