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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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    Application of the natural frequency estimation technique for mangosteen classification
    (2014-12-18)
    Leekul, P.
    ;
    Krairiksh, M.
    ;
    Sarkar, Tapan K.
    The problem of identifying unripe fruits using a non-destructive evaluation methodology is of great interest. In this paper the natural frequency estimation methodology described by the singularity expansion method (SEM) is used to evaluate the state of maturity of the mangosteen fruit using a non-destructive classification technique. The methodology is based on a RADAR identification technique based on the scattered field data is used to accomplish this goal. The classification is carried out using the SEM poles computed using the Cauchy method using the scattered field data for a mangosteen as it matures. Then, a pole library is constructed and is used in a classification scheme.