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Dual-Frequency Sensor for Thick Rind Fruit Quality Assessment
(2020-10-01)
Kittiyanpunya, Chainarong
;
Phongcharoenpanich, Chuwong
;
Krairiksh, Monai
This article proposes a novel multibeam dual-frequency sensor system to assess the quality of thick rind fruits based on phase difference between lower- and higher-frequency reflection coefficients ( Φ {12} ). The proposed sensor system consists of five dual-band antennas and a customized circuit that approximates lower- and higher-frequency phase difference. The main components of the customized circuit are down-conversion mixers and a phase detector module. For comparison, simulations were initially carried out using single- (1 GHz) and dual-frequency (1 GHz/2.3 GHz) sensor systems, and results indicated lower accuracy in classification of thick rind fruits of the single-frequency scheme. As a result, a dual-frequency sensor prototype was fabricated and experimented with normal and granulated plastic pomelo models and real pomelo fruits. The experimental results revealed that the average Φ{12} of the normal and granulated pomelos are almost identical, while the standard deviation (SD) of Φ 12 of the granulated pomelo is significantly larger than the normal pomelo. SD is thus used as the determinant of pomelo quality. The multibeam 1-GHz/2.3-GHz dual-frequency sensor system efficiently differentiates between normal and granulated pomelo fruits. As such, the proposed sensor system is operationally appropriate for quality control of thick rind fruits.
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A sensor for fruit classification using doppler radar
(2018-11-09)
Leekul, P.
;
Krairiksh, M.
This paper presents a microwave sensor that can detect defected fruits. In this work, mangosteen is used as an example. Translucent is detected by measuring Doppler frequency as mangosteen is rotated. From the simulated scattered waves at different directions around the fruits, the different in scattered wave results in Doppler signal from the defected fruit. The different D.C. voltage from the mixer identified whether there is translucent for the whole fruit. This cost effective sensor is a good candidate for fruit classification.
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A sensor for continuous fruit classification using Rician k-factor
(2018-07-02)
Leekul, Prapan
;
Krairiksh, Monai
The quality control in fruit industry is more and more demanded. For thick-peel fruit like durian, the UHF and microwave frequency bands are suitable. For a large number of fruits to be classified, a continuous process is desirable. The system using Rician k-factor has been analyzed and found to be feasible. This paper presents design and experimental results that describe the feature of a sensor system for fruit classification in a continuous process. The results show that the Rician k-factors from a single frequency-monostatic and wideband-bistatic measurements can be used as indicators for classifying maturity stage of durian fruits.
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Analysis of a sensor for fruit classification using Rician k-factor in a continuous process
(2017-01-12)
Leekul, P.
;
Krairiksh, M.
This paper presents simulation results that describes feature of a sensor system in a continuous process. The Rician k-factors from a single frequency-monostatic and a wideband-bistatic measurements can be used as indicators for classifying maturity stage of durian fruits.
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Microwave sensor for tangerine classification based on coupled-patch antennas
(2016-08-02)
Leekul, Prapan
;
Chivapreecha, Sorawat
;
Krairiksh, Monai
This paper deals with a microwave sensor for classifying tangerines by flavour using coupled-patch antennas. The operating frequency of the antennas is 2.45 GHz. The sensor determines the flavour of each tangerine by measuring the magnitudes of coupled signals of the antennas with the tangerine fruit at the centre. The sorting is carried out using an artificial neural network implemented on a field programmable gate array. The classification performance of the sensor is 95% accurate, so it has potential for use in sorting tangerines by flavour. In addition, the system uncertainty is analysed to determine optimal operating conditions.
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Microwave sensor for defected fruit classification
(2016-03-07)
Leekul, P.
;
Chivapreecha, S.
;
Krairiksh, M.
This paper presents a microwave sensor operating at the frequency of 2.45 GHz that can detect defected fruits. In this work, orange is used as an example. Granulation of orange is detected by measuring mean and standard deviation of the magnitudes of S-parameters of the orange at different positions. From the simulated S-parameters of patch antennas surrounding the fruits, it was found that the reflected signal from the fruit and the coupled signal to the antenna oriented perpendicular to the fruits provide the obvious variation and can be used as indicators for justification. This cost effective sensor is a good candidate for fruit classification.

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