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Moisture Content Measurement on Peanuts by using Time Domain Reflectometry
( Sheng Peng Niu ),( Tzu Hua Chen ),( Tse Min Chen ) 한국농업기계학회 2018 한국농업기계학회 학술발표논문집 Vol.23 No.1
The Moisture content detection of non-homogeneous materials has always been a challenge, especially for agricultural products with time varied characteristics and specific compositions. For in-shelled peanuts, this research developed a system with which is able to detect moisture content promptly. Peanuts with high quality have to keep dry in all kinds of phases such as harvesting, storage, and processing. To prevent mold from breeding and the spread of aflatoxin, which will influence the value and quality severely, the moisture content of peanuts is a key parameter to be monitored and controlled. Therefore, a highly efficient device or mechanism will be required. However, there is still no any devices with enough accuracy and promptness to detect moisture content for peanuts yet. This study employed TDR (Time Domain Reflectometry) technology to challenge this mission. Comparing with the results of traditional IR measurement and standard oven, which helps to set up a calibration curve, this research validates the proposed method to detect the moisture content of in-shell peanut finally.
( Yu-hung Lin ),( Tzu-fang Lai ),( Po-yen Lin ),( Tse-min Chen ) 한국농업기계학회 2018 한국농업기계학회 학술발표논문집 Vol.23 No.1
This research developed an integrated system that consist of orientation sensing, balance control, machine vision recognition and shape sorting and avoidance of obstacle with which the UVA will meet the requirement of a low altitude shuttle in orchards and forest. This research also focused on employing machine learning as the main control core to achieve the performances of target following and obstacle avoidance for unmanned aerial vehicle (UAV). In order to keep the balance of a quadcopter, the orientation data from gyroscope and accelerometer will be the inputs of a double loop PID controller. Target is recognized by machine vision. Distances and shapes of obstacles are defined by a laser rangefinder that mounted on the vehicle. The control of UAV depending on the shape of the obstacle, execute different obstacle avoidance strategies. The results of experiment indicated that the complementary filter can compensate the defects of the gyroscope and accelerometer since it fixes steady-state error of gyroscope and oscillation in high frequency of accelerometer. Double-loop PID controller is more stable than single-loop PID controller is. Due to the stability of control board and safety of operators in target following and obstacle avoidance experiment, a three wheels omni robot was employed to conduct the performance evaluation. The final results validate that the novel UAV is equipped with the ability of shuttling among orchards in low-altitude, target following, classification of obstacle shape and obstacle avoidance.