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Real-time Monitoring of Drying Parameters in Semi-Trailers during Peanut Drying

机译:花生干燥过程中半拖车干燥参数的实时监测

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The efficient control of drying parameters is essential to ensure that peanuts are dried at the optimal rate, preserving quality and desired flavor. The present peanut drying process has limitations in means for measuring parameters such as temperature and relative humidity of the air being blown into and exhausted from the peanuts in real-time or in a discrete manner. A sensor network, with an embedded microcontroller, consisting of relative humidity and temperature sensors and a microwave moisturesensor was developed to monitor such drying parameters in real-time. A previous version of the sensor network was field tested during the 2013 peanut harvest season, and positive results were observed. Drying parameters were measured and stored on a CompactFlash card every 12 seconds. In-shell kernel moisture content was determined with a standard error of prediction of 0.55% moisture when compared to the reference oven-drying method. After the addition of more sensors, two sensor networks were deployedduring the 2014 peanut harvest season at a peanut buying station in central Georgia. They were placed in the 45-ft drying semi-trailers with one near the front of the trailer and the other near the back of the trailer. At both locations, pod and kernelmoisture content, temperature of the drying peanuts, temperature and relative humidity of the air exhausted from the peanuts, and temperature and relative humidity of the air being blown into the peanuts were measured in real-time. Data from measurementsat the two locations within each semi-trailer were time-stamped and used to assess the uniformity of peanut drying. Results show promise for the development of a system to monitor and control drying parameters in the field in real-time. Such a system has the potential for saving a buying station on average $22,000/year in propane and electric energy costs.
机译:干燥参数的有效控制对于确保花生在最佳速率下干燥,保持质量和所需的味道是必不可少的。本发明的花生干燥过程具有用于测量诸如温度和吹入的空气的相对湿度的方法的限制,该参数在实时或以离散方式从花生中或以离散方式排出。具有由嵌入式微控制器的传感器网络,由相对湿度和温度传感器组成和微波潮湿体,以实时监测这种干燥参数。先前版本的传感器网络是在2013年花生收获季节测试的现场,并且观察到阳性结果。测量干燥参数并每12秒测量并储存在CompactFlash卡上。与参考烘箱干燥方法相比,用标准误差测定壳内核水分含量,预测0.55%的水分。添加更多的传感器后,两个传感器网络在格鲁吉亚中部的花生购买站部署了2014年花生收获季节。它们放在45英尺的烘干半拖车中,一个靠近拖车前面的一个,另一个在拖车后部附近。在各个位置,POD和核心缺陷含量,实时测量从花生排出的空气的温度,温度和相对湿度,以及空气中的温度和相对湿度被吹入花生进入花生。来自测量的数据,每个半拖车内的两个位置被时间冲压并用于评估花生干燥的均匀性。结果表明,在实时开发系统以监测和控制现场干燥参数的承诺。这种系统有可能以丙烷和电能成本平均每年节省购买站。

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